Aus-Property-Sales
Introduction
The realestate property sales data set which i’ve considered in this project belongs to HTAG. HtAG® is a web portal for real estate professionals that assists its customers in making property-related decisions based on timely and actionable market information. HtAG® leverages the benefits of machine learning algorithms to rank the growth potential of different Local Government Areas and suburbs, Australia wide. The data set analyzed can be obtained from the Kaggle platform. https://www.kaggle.com/htagholdings/aus-real-estate-sales-march-2019-to-april-2020/version/4 The data set includes all the closed sales data collected in the period of September 2018 and July 2020. The data provided includes major capital cities(Sydney, Melbourne, Brisbane, Adelaide, Perth, Canberra), Property_type (dwelling types: houses, units and townhouses), suburb, the latitude and longitude positions, locality (loc_pid) and Local government area (lga_pid).
Clearing the environment namespace for debugging purposes.
rm(list = ls())Command to tidy and un-attach any loaded packages so they don’t interact with this namespace
if (!is.null(sessionInfo()$otherPkgs)) {
invisible(
lapply(paste0('package:', names(sessionInfo()$otherPkgs)),
detach, character.only=TRUE, unload=TRUE)
)
}Load Libraries
library(ggplot2)
library(lattice)
library(gridExtra)
library(dplyr)##
## Attaching package: 'dplyr'## The following object is masked from 'package:gridExtra':
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## combine## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, unionlibrary(tidyverse)## -- Attaching packages ---------------------------------------------------------------------------------------------------------------------- tidyverse 1.3.0 --## v tibble 3.0.3 v purrr 0.3.4
## v tidyr 1.1.2 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.5.0## -- Conflicts ------------------------------------------------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::combine() masks gridExtra::combine()
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(psych)##
## Attaching package: 'psych'## The following objects are masked from 'package:ggplot2':
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## %+%, alphalibrary(timeDate)
library(lubridate)##
## Attaching package: 'lubridate'## The following objects are masked from 'package:base':
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## date, intersect, setdiff, unionlibrary(GGally)## Warning: package 'GGally' was built under R version 4.0.3## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2library(scales)##
## Attaching package: 'scales'## The following objects are masked from 'package:psych':
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## alpha, rescale## The following object is masked from 'package:purrr':
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## discard## The following object is masked from 'package:readr':
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## col_factorlibrary(VIM)## Loading required package: colorspace## Loading required package: grid## VIM is ready to use.## Suggestions and bug-reports can be submitted at: https://github.com/statistikat/VIM/issues##
## Attaching package: 'VIM'## The following object is masked from 'package:datasets':
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## sleepUsing R functions to explore the data.
Load the main data. I’ve stored the csv file within my project’s working directory.
rawdata.df <- read.csv('aus-property-sales-sep2018-april2020.csv', header = TRUE, sep = ',', stringsAsFactors = FALSE)
rawdata.dfUsing str to analyze the data
dim(rawdata.df)## [1] 320334 11str(rawdata.df)## 'data.frame': 320334 obs. of 11 variables:
## $ date_sold : chr "2018-09-18 00:00:00" "2018-09-24 00:00:00" "2018-09-26 00:00:00" "2018-09-26 00:00:00" ...
## $ price : chr "NULL" "NULL" "1730000" "1928000" ...
## $ suburb : chr "Darling Point" "Darling Point" "Darling Point" "Darling Point" ...
## $ city_name : chr "Sydney" "Sydney" "Sydney" "Sydney" ...
## $ state : chr "NSW" "NSW" "NSW" "NSW" ...
## $ lat : chr "-33.869565" "-33.872179" "-33.868386" "-33.875465" ...
## $ lon : chr "151.241317" "151.239726" "151.237471" "151.23628" ...
## $ bedrooms : int 3 3 2 3 3 2 3 2 3 3 ...
## $ property_type: chr "unit" "unit" "unit" "unit" ...
## $ loc_pid : chr "NSW1221" "NSW1221" "NSW1221" "NSW1221" ...
## $ lga_pid : chr "NSW180" "NSW180" "NSW180" "NSW180" ...There are 320334 observations with 11 variables, comprising 1 integer and 10 Characters. Using describe to analyze the data
describe(rawdata.df)Using summary to analyze the data
summary(rawdata.df)## date_sold price suburb city_name
## Length:320334 Length:320334 Length:320334 Length:320334
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## state lat lon bedrooms
## Length:320334 Length:320334 Length:320334 Min. :0.000
## Class :character Class :character Class :character 1st Qu.:2.000
## Mode :character Mode :character Mode :character Median :3.000
## Mean :3.109
## 3rd Qu.:4.000
## Max. :5.000
## property_type loc_pid lga_pid
## Length:320334 Length:320334 Length:320334
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
## To see the first ten and the last ten observations in the dataset
head(rawdata.df, 10)tail(rawdata.df, 10)Using apply function to check for any NA’s in the data set
apply(is.na(rawdata.df),2, sum)## date_sold price suburb city_name state
## 0 0 0 0 0
## lat lon bedrooms property_type loc_pid
## 0 0 0 0 0
## lga_pid
## 0Using sapply to for the class of the variables
sapply(rawdata.df, class)## date_sold price suburb city_name state
## "character" "character" "character" "character" "character"
## lat lon bedrooms property_type loc_pid
## "character" "character" "integer" "character" "character"
## lga_pid
## "character"Finding the Unique values of the variables
unique(rawdata.df$state)## [1] "NSW" "VIC" "WA" "SA" "QLD" "ACT"unique(rawdata.df$city_name)## [1] "Sydney" "Melbourne" "Perth" "Adelaide" "Brisbane" "Canberra"unique(rawdata.df$property_type)## [1] "unit" "house" "townhouse"unique(rawdata.df$bedrooms)## [1] 3 2 1 0 5 4Finding the total number of properties sold from September 2018 to July 2020 state wise and also the number of properties sold suburb wise in all the states
table(rawdata.df$state, dnn = "Properties sold from Sept 2018 to July 2020")## Properties sold from Sept 2018 to July 2020
## ACT NSW QLD SA VIC WA
## 11101 85295 32240 32857 119180 39661table(rawdata.df$suburb, rawdata.df$state , dnn="Number of Properties sold by Suburb")## NA
## Number of Properties sold by Suburb ACT NSW QLD SA VIC WA
## Abbotsbury 0 35 0 0 0 0
## Abbotsford 0 106 0 0 300 0
## Aberfeldie 0 0 0 0 82 0
## Aberfoyle Park 0 0 0 259 0 0
## Acacia Gardens 0 78 0 0 0 0
## Acacia Ridge 0 0 149 0 0 0
## Acton 5 0 0 0 0 0
## Adelaide 0 0 0 737 0 0
## Ainslie 97 0 0 0 0 0
## Airds 0 74 0 0 0 0
## Airport West 0 0 0 0 248 0
## Albanvale 0 0 0 0 92 0
## Albert Park 0 0 0 50 183 0
## Alberton 0 0 0 54 0 0
## Albion 0 0 88 0 142 0
## Alderley 0 0 214 0 0 0
## Aldgate 0 0 0 86 0 0
## Aldinga 0 0 0 15 0 0
## Aldinga Beach 0 0 0 348 0 0
## Alexander Heights 0 0 0 0 0 136
## Alexandria 0 276 0 0 0 0
## Alfords Point 0 49 0 0 0 0
## Alfred Cove 0 0 0 0 0 76
## Algester 0 0 224 0 0 0
## Alkimos 0 0 0 0 0 170
## Allambie Heights 0 117 0 0 0 0
## Allawah 0 95 0 0 0 0
## Allenby Gardens 0 0 0 38 0 0
## Alphington 0 0 0 0 122 0
## Altona 0 0 0 0 402 0
## Altona Meadows 0 0 0 0 345 0
## Altona North 0 0 0 0 373 0
## Amaroo 119 0 0 0 0 0
## Ambarvale 0 119 0 0 0 0
## Andrews Farm 0 0 0 237 0 0
## Angle Park 0 0 0 24 0 0
## Angle Vale 0 0 0 41 0 0
## Anketell 0 0 0 0 0 2
## Annandale 0 229 0 0 0 0
## Annangrove 0 7 0 0 0 0
## Annerley 0 0 343 0 0 0
## Anstead 0 0 17 0 0 0
## Applecross 0 0 0 0 0 194
## Aranda 42 0 0 0 0 0
## Arcadia 0 12 0 0 0 0
## Archerfield 0 0 15 0 0 0
## Ardeer 0 0 0 0 84 0
## Ardross 0 0 0 0 0 120
## Armadale 0 0 0 0 319 272
## Arncliffe 0 180 0 0 0 0
## Artarmon 0 186 0 0 0 0
## Arthurs Creek 0 0 0 0 5 0
## Arthurs Seat 0 0 0 0 15 0
## Ascot 0 0 0 0 0 62
## Ascot Park 0 0 0 139 0 0
## Ascot Vale 0 0 0 0 385 0
## Ashburton 0 0 0 0 169 0
## Ashbury 0 42 0 0 0 0
## Ashby 0 0 0 0 0 51
## Ashcroft 0 37 0 0 0 0
## Ashfield 0 412 0 0 0 32
## Ashford 0 0 0 33 0 0
## Ashgrove 0 0 326 0 0 0
## Ashton 0 0 0 3 0 0
## Ashwood 0 0 0 0 162 0
## Aspendale 0 0 0 0 191 0
## Aspendale Gardens 0 0 0 0 80 0
## Aspley 0 0 335 0 0 0
## Asquith 0 136 0 0 0 0
## Athol Park 0 0 0 41 0 0
## Attadale 0 0 0 0 0 149
## Attwood 0 0 0 0 48 0
## Atwell 0 0 0 0 0 191
## Aubin Grove 0 0 0 0 0 125
## Auburn 0 430 0 0 0 0
## Auchenflower 0 0 202 0 0 0
## Auldana 0 0 0 8 0 0
## Austral 0 93 0 0 0 0
## Avalon Beach 0 317 0 0 0 0
## Aveley 0 0 0 0 0 241
## Avondale Heights 0 0 0 0 235 0
## Avonsleigh 0 0 0 0 24 0
## Badger Creek 0 0 0 0 20 0
## Balaclava 0 0 0 0 121 0
## Balcatta 0 0 0 0 0 158
## Bald Hills 0 0 153 0 0 0
## Baldivis 0 0 0 0 0 760
## Balga 0 0 0 0 0 207
## Balgowlah 0 243 0 0 0 0
## Balgowlah Heights 0 73 0 0 0 0
## Balhannah 0 0 0 39 0 0
## Ballajura 0 0 0 0 0 268
## Balmain 0 326 0 0 0 0
## Balmain East 0 52 0 0 0 0
## Balmoral 0 0 156 0 0 0
## Balnarring 0 0 0 0 56 0
## Balnarring Beach 0 0 0 0 15 0
## Balwyn 0 0 0 0 363 0
## Balwyn North 0 0 0 0 502 0
## Bangholme 0 0 0 0 5 0
## Bangor 0 102 0 0 0 0
## Banjup 0 0 0 0 0 20
## Banks 145 0 0 0 0 0
## Banksia 0 50 0 0 0 0
## Banksia Grove 0 0 0 0 0 195
## Banksia Park 0 0 0 77 0 0
## Bankstown 0 482 0 0 0 0
## Banyo 0 0 150 0 0 0
## Barangaroo 0 4 0 0 0 0
## Barden Ridge 0 67 0 0 0 0
## Bardia 0 69 0 0 0 0
## Bardon 0 0 323 0 0 0
## Bardwell Park 0 28 0 0 0 0
## Bardwell Valley 0 34 0 0 0 0
## Barton 71 0 0 0 0 0
## Basket Range 0 0 0 2 0 0
## Bass Hill 0 109 0 0 0 0
## Bassendean 0 0 0 0 0 261
## Bateman 0 0 0 0 0 50
## Baulkham Hills 0 767 0 0 0 0
## Baxter 0 0 0 0 63 0
## Bayles 0 0 0 0 3 0
## Bayswater 0 0 0 0 353 331
## Bayswater North 0 0 0 0 255 0
## Bayview 0 71 0 0 0 0
## Beacon Hill 0 115 0 0 0 0
## Beaconsfield 0 25 0 0 197 109
## Beaconsfield Upper 0 0 0 0 47 0
## Beaumaris 0 0 0 0 373 0
## Beaumont 0 0 0 79 0 0
## Beaumont Hills 0 179 0 0 0 0
## Beckenham 0 0 0 0 0 118
## Bedford 0 0 0 0 0 134
## Bedford Park 0 0 0 31 0 0
## Bedfordale 0 0 0 0 0 67
## Beechboro 0 0 0 0 0 151
## Beechina 0 0 0 0 0 1
## Beecroft 0 199 0 0 0 0
## Beeliar 0 0 0 0 0 145
## Belair 0 0 0 95 0 0
## Belconnen 251 0 0 0 0 0
## Beldon 0 0 0 0 0 100
## Belfield 0 75 0 0 0 0
## Belgrave 0 0 0 0 111 0
## Belgrave Heights 0 0 0 0 29 0
## Belgrave South 0 0 0 0 21 0
## Bella Vista 0 127 0 0 0 0
## Bellbowrie 0 0 126 0 0 0
## Bellevue 0 0 0 0 0 38
## Bellevue Heights 0 0 0 63 0 0
## Bellevue Hill 0 326 0 0 0 0
## Bellfield 0 0 0 0 46 0
## Belmont 0 0 117 0 0 135
## Belmore 0 164 0 0 0 0
## Belrose 0 126 0 0 0 0
## Bend Of Islands 0 0 0 0 5 0
## Bennett Springs 0 0 0 0 0 76
## Bentleigh 0 0 0 0 546 0
## Bentleigh East 0 0 0 0 778 0
## Bentley 0 0 0 0 0 134
## Berala 0 104 0 0 0 0
## Berkshire Park 0 1 0 0 0 0
## Berowra 0 80 0 0 0 0
## Berowra Heights 0 77 0 0 0 0
## Berowra Waters 0 7 0 0 0 0
## Bertram 0 0 0 0 0 104
## Berwick 0 0 0 0 1190 0
## Beulah Park 0 0 0 59 0 0
## Beverley 0 0 0 36 0 0
## Beverley Park 0 30 0 0 0 0
## Beverly Hills 0 131 0 0 0 0
## Bexley 0 265 0 0 0 0
## Bexley North 0 54 0 0 0 0
## Bibaringa 0 0 0 4 0 0
## Bibra Lake 0 0 0 0 0 92
## Bickley 0 0 0 0 0 8
## Bickley Vale 0 1 0 0 0 0
## Bicton 0 0 0 0 0 163
## Bidwill 0 32 0 0 0 0
## Big Pats Creek 0 0 0 0 5 0
## Bilgola Beach 0 5 0 0 0 0
## Bilgola Plateau 0 76 0 0 0 0
## Birchgrove 0 94 0 0 0 0
## Birkenhead 0 0 0 45 0 0
## Birrong 0 22 0 0 0 0
## Bittern 0 0 0 0 113 0
## Black Forest 0 0 0 42 0 0
## Black Rock 0 0 0 0 180 0
## Blackburn 0 0 0 0 407 0
## Blackburn North 0 0 0 0 198 0
## Blackburn South 0 0 0 0 215 0
## Blackett 0 45 0 0 0 0
## Blacktown 0 887 0 0 0 0
## Blackwood 0 0 0 111 0 0
## Blair Athol 0 36 0 97 0 0
## Blairgowrie 0 0 0 0 214 0
## Blairmount 0 2 0 0 0 0
## Blakehurst 0 103 0 0 0 0
## Blakeview 0 0 0 238 0 0
## Blewitt Springs 0 0 0 4 0 0
## Blind Bight 0 0 0 0 31 0
## Bonbeach 0 0 0 0 248 0
## Bondi 0 273 0 0 0 0
## Bondi Beach 0 339 0 0 0 0
## Bondi Junction 0 265 0 0 0 0
## Bonner 156 0 0 0 0 0
## Bonnet Bay 0 51 0 0 0 0
## Bonnyrigg 0 77 0 0 0 0
## Bonnyrigg Heights 0 44 0 0 0 0
## Bonython 95 0 0 0 0 0
## Boondall 0 0 240 0 0 0
## Booragoon 0 0 0 0 0 102
## Boronia 0 0 0 0 690 0
## Bossley Park 0 129 0 0 0 0
## Botanic Ridge 0 0 0 0 186 0
## Botany 0 262 0 0 0 0
## Bow Bowing 0 30 0 0 0 0
## Bowden 0 0 0 55 0 0
## Bowen Hills 0 0 88 0 0 0
## Box Hill 0 204 0 0 344 0
## Box Hill North 0 0 0 0 301 0
## Box Hill South 0 0 0 0 231 0
## Boya 0 0 0 0 0 20
## Brabham 0 0 0 0 0 133
## Bracken Ridge 0 0 483 0 0 0
## Bradbury 0 208 0 0 0 0
## Braddon 261 0 0 0 0 0
## Brahma Lodge 0 0 0 75 0 0
## Braybrook 0 0 0 0 179 0
## Breakfast Point 0 165 0 0 0 0
## Brentwood 0 0 0 0 0 49
## Briar Hill 0 0 0 0 80 0
## Bridgeman Downs 0 0 213 0 0 0
## Brigadoon 0 0 0 0 0 16
## Brighton 0 0 367 125 714 0
## Brighton-Le-Sands 0 181 0 0 0 0
## Brighton East 0 0 0 0 407 0
## Bringelly 0 8 0 0 0 0
## Brisbane City 0 0 561 0 0 0
## Broadmeadows 0 0 0 0 242 0
## Broadview 0 0 0 133 0 0
## Brompton 0 0 0 110 0 0
## Bronte 0 179 0 0 0 0
## Brookdale 0 0 0 0 0 44
## Brookfield 0 0 60 0 254 0
## Brooklyn 0 21 0 0 89 0
## Brooklyn Park 0 0 0 119 0 0
## Brookvale 0 149 0 0 0 0
## Bruce 215 0 0 0 0 0
## Brunswick 0 0 0 0 710 0
## Brunswick East 0 0 0 0 413 0
## Brunswick West 0 0 0 0 389 0
## Buckland Park 0 0 0 2 0 0
## Bulimba 0 0 362 0 0 0
## Bull Creek 0 0 0 0 0 112
## Bulla 0 0 0 0 8 0
## Bulleen 0 0 0 0 267 0
## Bullsbrook 0 0 0 0 0 83
## Bundeena 0 36 0 0 0 0
## Bundoora 0 0 0 0 562 0
## Bungarribee 0 17 0 0 0 0
## Bunyip 0 0 0 0 54 0
## Burbank 0 0 14 0 0 0
## Burnley 0 0 0 0 2 0
## Burns Beach 0 0 0 0 0 119
## Burnside 0 0 0 86 74 0
## Burnside Heights 0 0 0 0 96 0
## Burraneer 0 68 0 0 0 0
## Burswood 0 0 0 0 0 62
## Burton 0 0 0 144 0 0
## Burwood 0 224 0 0 334 0
## Burwood East 0 0 0 0 199 0
## Burwood Heights 0 19 0 0 0 0
## Busby 0 49 0 0 0 0
## Bushmead 0 0 0 0 0 12
## Butler 0 0 0 0 0 293
## Byford 0 0 0 0 0 319
## Cabarita 0 34 0 0 0 0
## Cabramatta 0 190 0 0 0 0
## Cabramatta West 0 55 0 0 0 0
## Caddens 0 36 0 0 0 0
## Cairnlea 0 0 0 0 114 0
## Calamvale 0 0 445 0 0 0
## Caldermeade 0 0 0 0 1 0
## Calista 0 0 0 0 0 27
## Calwell 135 0 0 0 0 0
## Camberwell 0 0 0 0 488 0
## Cambridge Gardens 0 38 0 0 0 0
## Cambridge Park 0 164 0 0 0 0
## Camden 0 77 0 0 0 0
## Camden Park 0 0 0 124 0 0
## Camden South 0 101 0 0 0 0
## Camillo 0 0 0 0 0 81
## Cammeray 0 199 0 0 0 0
## Camp Hill 0 0 464 0 0 0
## Campbell 126 0 0 0 0 0
## Campbellfield 0 0 0 0 53 0
## Campbelltown 0 348 0 0 0 0
## Camperdown 0 260 0 0 0 0
## Campsie 0 319 0 0 0 0
## Canada Bay 0 27 0 0 0 0
## Canley Heights 0 99 0 0 0 0
## Canley Vale 0 98 0 0 0 0
## Canning Vale 0 0 0 0 0 558
## Cannington 0 0 0 0 0 92
## Cannon Hill 0 0 199 0 0 0
## Cannons Creek 0 0 0 0 16 0
## Canterbury 0 132 0 0 188 0
## Cape Schanck 0 0 0 0 25 0
## Capel Sound 0 0 0 0 192 0
## Cardinia 0 0 0 0 5 0
## Cardup 0 0 0 0 0 11
## Carey Gully 0 0 0 4 0 0
## Carina 0 0 398 0 0 0
## Carina Heights 0 0 262 0 0 0
## Carindale 0 0 351 0 0 0
## Carine 0 0 0 0 0 127
## Caringbah 0 382 0 0 0 0
## Caringbah South 0 291 0 0 0 0
## Carlingford 0 406 0 0 0 0
## Carlisle 0 0 0 0 0 114
## Carlton 0 169 0 0 370 0
## Carlton North 0 0 0 0 157 0
## Carmel 0 0 0 0 0 7
## Carnegie 0 0 0 0 479 0
## Carnes Hill 0 26 0 0 0 0
## Caroline Springs 0 0 0 0 533 0
## Carramar 0 39 0 0 0 144
## Carrum 0 0 0 0 163 0
## Carrum Downs 0 0 0 0 672 0
## Carseldine 0 0 219 0 0 0
## Carss Park 0 20 0 0 0 0
## Cartwright 0 20 0 0 0 0
## Casey 198 0 0 0 0 0
## Castle Cove 0 44 0 0 0 0
## Castle Hill 0 784 0 0 0 0
## Castlecrag 0 59 0 0 0 0
## Castlereagh 0 1 0 0 0 0
## Casuarina 0 0 0 0 0 9
## Casula 0 220 0 0 0 0
## Catani 0 0 0 0 1 0
## Catherine Field 0 15 0 0 0 0
## Caulfield 0 0 0 0 143 0
## Caulfield East 0 0 0 0 42 0
## Caulfield North 0 0 0 0 352 0
## Caulfield South 0 0 0 0 255 0
## Caversham 0 0 0 0 0 117
## Cecil Hills 0 70 0 0 0 0
## Cecil Park 0 3 0 0 0 0
## Centennial Park 0 82 0 0 0 0
## Chadstone 0 0 0 0 247 0
## Champion Lakes 0 0 0 0 0 15
## Chandler 0 0 21 0 0 0
## Chandlers Hill 0 0 0 15 0 0
## Chapel Hill 0 0 232 0 0 0
## Chapman 57 0 0 0 0 0
## Charleston 0 0 0 11 0 0
## Charnwood 73 0 0 0 0 0
## Chatswood 0 438 0 0 0 0
## Chatswood West 0 4 0 0 0 0
## Chelmer 0 0 83 0 0 0
## Chelsea 0 0 0 0 322 0
## Chelsea Heights 0 0 0 0 118 0
## Cheltenham 0 23 0 57 664 0
## Chermside 0 0 296 0 0 0
## Chermside West 0 0 182 0 0 0
## Cherry Gardens 0 0 0 4 0 0
## Cherrybrook 0 279 0 0 0 0
## Cherryville 0 0 0 2 0 0
## Chester Hill 0 147 0 0 0 0
## Chidlow 0 0 0 0 0 39
## Chifley 86 48 0 0 0 0
## Chippendale 0 152 0 0 0 0
## Chipping Norton 0 155 0 0 0 0
## Chirnside Park 0 0 0 0 294 0
## Chisholm 112 0 0 0 0 0
## Chiswick 0 102 0 0 0 0
## Christie Downs 0 0 0 100 0 0
## Christies Beach 0 0 0 211 0 0
## Christmas Hills 0 0 0 0 4 0
## Chum Creek 0 0 0 0 14 0
## Church Point 0 28 0 0 0 0
## Churchlands 0 0 0 0 0 90
## City 141 0 0 0 0 0
## City Beach 0 0 0 0 0 151
## Clapham 0 0 0 42 0 0
## Claremont 0 0 0 0 0 291
## Claremont Meadows 0 85 0 0 0 0
## Clarence Gardens 0 0 0 41 0 0
## Clarence Park 0 0 0 70 0 0
## Clarendon 0 0 0 11 0 0
## Clareville 0 11 0 0 0 0
## Clarinda 0 0 0 0 123 0
## Clarkson 0 0 0 0 0 310
## Clayfield 0 0 328 0 0 0
## Claymore 0 16 0 0 0 0
## Clayton 0 0 0 0 349 0
## Clayton South 0 0 0 0 263 0
## Clearview 0 0 0 99 0 0
## Clematis 0 0 0 0 10 0
## Clemton Park 0 20 0 0 0 0
## Clifton Hill 0 0 0 0 152 0
## Clontarf 0 44 0 0 0 0
## Clovelly 0 129 0 0 0 0
## Clovelly Park 0 0 0 86 0 0
## Cloverdale 0 0 0 0 0 168
## Clyde 0 0 0 0 262 0
## Clyde North 0 0 0 0 705 0
## Coasters Retreat 0 5 0 0 0 0
## Cobbitty 0 142 0 0 0 0
## Coburg 0 0 0 0 611 0
## Coburg North 0 0 0 0 216 0
## Cockatoo 0 0 0 0 116 0
## Cockburn Central 0 0 0 0 0 28
## Coldstream 0 0 0 0 47 0
## Colebee 0 56 0 0 0 0
## Collaroy 0 232 0 0 0 0
## Collaroy Plateau 0 109 0 0 0 0
## College Park 0 0 0 12 0 0
## Collingwood 0 0 0 0 310 0
## Collinswood 0 0 0 43 0 0
## Colonel Light Gardens 0 0 0 68 0 0
## Colyton 0 147 0 0 0 0
## Como 0 74 0 0 0 348
## Concord 0 238 0 0 0 0
## Concord West 0 79 0 0 0 0
## Condell Park 0 119 0 0 0 0
## Conder 114 0 0 0 0 0
## Connells Point 0 37 0 0 0 0
## Connolly 0 0 0 0 0 73
## Constitution Hill 0 43 0 0 0 0
## Coogee 0 417 0 0 0 83
## Cook 82 0 0 0 0 0
## Coolaroo 0 0 0 0 40 0
## Coolbellup 0 0 0 0 0 139
## Coolbinia 0 0 0 0 0 38
## Cooloongup 0 0 0 0 0 148
## Coombs 100 0 0 0 0 0
## Coopers Plains 0 0 107 0 0 0
## Coorparoo 0 0 560 0 0 0
## Cora Lynn 0 0 0 0 1 0
## Corinda 0 0 136 0 0 0
## Coromandel East 0 0 0 2 0 0
## Coromandel Valley 0 0 0 109 0 0
## Cottage Point 0 5 0 0 0 0
## Cottesloe 0 0 0 0 0 214
## Cottles Bridge 0 0 0 0 5 0
## Cowan 0 7 0 0 0 0
## Cowandilla 0 0 0 30 0 0
## Crace 107 0 0 0 0 0
## Crafers 0 0 0 50 0 0
## Crafers West 0 0 0 40 0 0
## Craigburn Farm 0 0 0 72 0 0
## Craigie 0 0 0 0 0 146
## Craigieburn 0 0 0 0 1502 0
## Craigmore 0 0 0 249 0 0
## Cranbourne 0 0 0 0 548 0
## Cranbourne East 0 0 0 0 467 0
## Cranbourne North 0 0 0 0 615 0
## Cranbourne South 0 0 0 0 20 0
## Cranbourne West 0 0 0 0 552 0
## Cranebrook 0 333 0 0 0 0
## Crawley 0 0 0 0 0 62
## Cremorne 0 376 0 0 9 0
## Cremorne Point 0 49 0 0 0 0
## Crib Point 0 0 0 0 125 0
## Cromer 0 132 0 0 0 0
## Cronulla 0 601 0 0 0 0
## Crows Nest 0 150 0 0 0 0
## Croydon 0 142 0 17 939 0
## Croydon Hills 0 0 0 0 96 0
## Croydon North 0 0 0 0 224 0
## Croydon Park 0 173 0 84 0 0
## Croydon South 0 0 0 0 135 0
## Cudlee Creek 0 0 0 2 0 0
## Cumberland Park 0 0 0 71 0 0
## Curl Curl 0 66 0 0 0 0
## Currambine 0 0 0 0 0 153
## Currans Hill 0 124 0 0 0 0
## Curtin 126 0 0 0 0 0
## Daceyville 0 9 0 0 0 0
## Daglish 0 0 0 0 0 44
## Dalkeith 0 0 0 0 0 106
## Dallas 0 0 0 0 122 0
## Dalmore 0 0 0 0 1 0
## Dandenong 0 0 0 0 602 0
## Dandenong North 0 0 0 0 366 0
## Dangar Island 0 11 0 0 0 0
## Darch 0 0 0 0 0 123
## Darling Downs 0 0 0 0 0 19
## Darling Point 0 135 0 0 0 0
## Darlinghurst 0 317 0 0 0 0
## Darlington 0 42 0 28 0 92
## Darra 0 0 85 0 0 0
## Davidson 0 50 0 0 0 0
## Davoren Park 0 0 0 135 0 0
## Daw Park 0 0 0 95 0 0
## Dayton 0 0 0 0 0 57
## Deagon 0 0 138 0 0 0
## Deakin 72 0 0 0 0 0
## Dean Park 0 53 0 0 0 0
## Dee Why 0 829 0 0 0 0
## Deepdene 0 0 0 0 30 0
## Deer Park 0 0 0 0 397 0
## Delahey 0 0 0 0 139 0
## Denham Court 0 152 0 0 0 0
## Denistone 0 54 0 0 0 0
## Denistone East 0 35 0 0 0 0
## Denistone West 0 9 0 0 0 0
## Denman Prospect 16 0 0 0 0 0
## Dernancourt 0 0 0 99 0 0
## Derrimut 0 0 0 0 147 0
## Devon Meadows 0 0 0 0 16 0
## Devon Park 0 0 0 36 0 0
## Dewhurst 0 0 0 0 1 0
## Dharruk 0 41 0 0 0 0
## Diamond Creek 0 0 0 0 317 0
## Dianella 0 0 0 0 0 463
## Dickson 89 0 0 0 0 0
## Diggers Rest 0 0 0 0 100 0
## Dingley Village 0 0 0 0 178 0
## Direk 0 0 0 17 0 0
## Dixons Creek 0 0 0 0 3 0
## Docklands 0 0 0 0 612 0
## Dolans Bay 0 15 0 0 0 0
## Dolls Point 0 48 0 0 0 0
## Don Valley 0 0 0 0 9 0
## Doncaster 0 0 0 0 724 0
## Doncaster East 0 0 0 0 682 0
## Donnybrook 0 0 0 0 27 0
## Donvale 0 0 0 0 322 0
## Doolandella 0 0 103 0 0 0
## Doonside 0 171 0 0 0 0
## Doreen 0 0 0 0 799 0
## Double Bay 0 171 0 0 0 0
## Doubleview 0 0 0 0 0 253
## Dover Gardens 0 0 0 107 0 0
## Dover Heights 0 99 0 0 0 0
## Doveton 0 0 0 0 241 0
## Downer 76 0 0 0 0 0
## Drewvale 0 0 99 0 0 0
## Dromana 0 0 0 0 257 0
## Drummoyne 0 297 0 0 0 0
## Dry Creek 0 0 0 6 0 0
## Dudley Park 0 0 0 7 0 0
## Duffy 82 0 0 0 0 0
## Duffys Forest 0 7 0 0 0 0
## Dulwich 0 0 0 34 0 0
## Dulwich Hill 0 284 0 0 0 0
## Duncraig 0 0 0 0 0 360
## Dundas 0 75 0 0 0 0
## Dundas Valley 0 81 0 0 0 0
## Dunlop 166 0 0 0 0 0
## Durack 0 0 101 0 0 0
## Dural 0 104 0 0 0 0
## Dutton Park 0 0 43 0 0 0
## Eagle Vale 0 83 0 0 0 0
## Eaglemont 0 0 0 0 99 0
## Earlwood 0 250 0 0 0 0
## East Brisbane 0 0 165 0 0 0
## East Cannington 0 0 0 0 0 90
## East Fremantle 0 0 0 0 0 202
## East Hills 0 45 0 0 0 0
## East Killara 0 27 0 0 0 0
## East Lindfield 0 54 0 0 0 0
## East Melbourne 0 0 0 0 163 0
## East Perth 0 0 0 0 0 363
## East Ryde 0 45 0 0 0 0
## East Victoria Park 0 0 0 0 0 232
## East Warburton 0 0 0 0 42 0
## Eastern Creek 0 14 0 0 0 0
## Eastgardens 0 13 0 0 0 0
## Eastlakes 0 94 0 0 0 0
## Eastwood 0 250 0 28 0 0
## Eden Hill 0 0 0 0 0 74
## Eden Hills 0 0 0 67 0 0
## Eden Park 0 0 0 0 16 0
## Edensor Park 0 69 0 0 0 0
## Edgecliff 0 79 0 0 0 0
## Edgewater 0 0 0 0 0 110
## Edithvale 0 0 0 0 219 0
## Edmondson Park 0 137 0 0 0 0
## Edwardstown 0 0 0 130 0 0
## Eglinton 0 0 0 0 0 45
## Eight Mile Plains 0 0 252 0 0 0
## Elanora Heights 0 71 0 0 0 0
## Elderslie 0 177 0 0 0 0
## Elizabeth 0 0 0 26 0 0
## Elizabeth Bay 0 193 0 0 0 0
## Elizabeth Downs 0 0 0 139 0 0
## Elizabeth East 0 0 0 104 0 0
## Elizabeth Grove 0 0 0 63 0 0
## Elizabeth Hills 0 24 0 0 0 0
## Elizabeth North 0 0 0 100 0 0
## Elizabeth Park 0 0 0 113 0 0
## Elizabeth South 0 0 0 51 0 0
## Elizabeth Vale 0 0 0 88 0 0
## Ellen Grove 0 0 44 0 0 0
## Ellenbrook 0 0 0 0 0 417
## Ellis Lane 0 14 0 0 0 0
## Elsternwick 0 0 0 0 291 0
## Eltham 0 0 0 0 454 0
## Eltham North 0 0 0 0 129 0
## Elvina Bay 0 2 0 0 0 0
## Elwood 0 0 0 0 578 0
## Embleton 0 0 0 0 0 60
## Emerald 0 0 0 0 149 0
## Emerton 0 36 0 0 0 0
## Emu Heights 0 51 0 0 0 0
## Emu Plains 0 150 0 0 0 0
## Endeavour Hills 0 0 0 0 466 0
## Enfield 0 52 0 148 0 0
## Engadine 0 370 0 0 0 0
## Englorie Park 0 9 0 0 0 0
## Enmore 0 91 0 0 0 0
## Enoggera 0 0 144 0 0 0
## Enoggera Reservoir 0 0 1 0 0 0
## Epping 0 514 0 0 648 0
## Erindale 0 0 0 35 0 0
## Ermington 0 186 0 0 0 0
## Erskine Park 0 108 0 0 0 0
## Erskineville 0 253 0 0 0 0
## Eschol Park 0 64 0 0 0 0
## Essendon 0 0 0 0 590 0
## Essendon North 0 0 0 0 87 0
## Essendon West 0 0 0 0 36 0
## Ethelton 0 0 0 36 0 0
## Eumemmerring 0 0 0 0 69 0
## Evandale 0 0 0 32 0 0
## Evanston 0 0 0 77 0 0
## Evanston Gardens 0 0 0 57 0 0
## Evanston Park 0 0 0 95 0 0
## Evanston South 0 0 0 12 0 0
## Evatt 99 0 0 0 0 0
## Eveleigh 0 5 0 0 0 0
## Everard Park 0 0 0 30 0 0
## Everton Park 0 0 327 0 0 0
## Exeter 0 0 0 25 0 0
## Eynesbury 0 0 0 0 97 0
## Eyre 0 0 0 8 0 0
## Fadden 79 0 0 0 0 0
## Fairfield 0 220 102 0 171 0
## Fairfield East 0 31 0 0 0 0
## Fairfield Heights 0 67 0 0 0 0
## Fairfield West 0 117 0 0 0 0
## Fairlight 0 226 0 0 0 0
## Fairview Park 0 0 0 85 0 0
## Farrer 87 0 0 0 0 0
## Fawkner 0 0 0 0 292 0
## Felixstow 0 0 0 74 0 0
## Ferndale 0 0 0 0 0 83
## Ferntree Gully 0 0 0 0 636 0
## Ferny Creek 0 0 0 0 40 0
## Ferny Grove 0 0 123 0 0 0
## Ferryden Park 0 0 0 66 0 0
## Fig Tree Pocket 0 0 98 0 0 0
## Findon 0 0 0 179 0 0
## Fingal 0 0 0 0 40 0
## Firle 0 0 0 24 0 0
## Fisher 74 0 0 0 0 0
## Fitzgibbon 0 0 186 0 0 0
## Fitzroy 0 0 0 11 274 0
## Fitzroy North 0 0 0 0 270 0
## Five Dock 0 193 0 0 0 0
## Flagstaff Hill 0 0 0 236 0 0
## Flemington 0 0 0 0 182 0
## Flinders 0 0 0 0 62 0
## Flinders Park 0 0 0 133 0 0
## Floreat 0 0 0 0 0 203
## Florey 94 0 0 0 0 0
## Flynn 73 0 0 0 0 0
## Footscray 0 0 0 0 488 0
## Forde 141 0 0 0 0 0
## Forest Hill 0 0 0 0 244 0
## Forest Lake 0 0 636 0 0 0
## Forest Lodge 0 106 0 0 0 0
## Forest Range 0 0 0 4 0 0
## Forestville 0 147 0 31 0 0
## Forrest 56 0 0 0 0 0
## Forrestdale 0 0 0 0 0 15
## Forrestfield 0 0 0 0 0 259
## Forreston 0 0 0 5 0 0
## Fortitude Valley 0 0 246 0 0 0
## Franklin 227 0 0 0 0 0
## Frankston 0 0 0 0 1344 0
## Frankston North 0 0 0 0 175 0
## Frankston South 0 0 0 0 509 0
## Fraser 36 0 0 0 0 0
## Fraser Rise 0 0 0 0 169 0
## Fremantle 0 0 0 0 0 246
## Frenchs Forest 0 260 0 0 0 0
## Freshwater 0 298 0 0 0 0
## Frewville 0 0 0 24 0 0
## Fulham 0 0 0 68 0 0
## Fulham Gardens 0 0 0 122 0 0
## Fullarton 0 0 0 115 0 0
## Galston 0 54 0 0 0 0
## Gardenvale 0 0 0 0 23 0
## Garfield 0 0 0 0 40 0
## Garran 79 0 0 0 0 0
## Gawler 0 0 0 41 0 0
## Gawler East 0 0 0 170 0 0
## Gawler South 0 0 0 98 0 0
## Gawler West 0 0 0 32 0 0
## Gaythorne 0 0 112 0 0 0
## Geebung 0 0 127 0 0 0
## Gembrook 0 0 0 0 70 0
## Georges Hall 0 140 0 0 0 0
## Gepps Cross 0 0 0 10 0 0
## Gidgegannup 0 0 0 0 0 40
## Gilberton 0 0 0 46 0 0
## Gilderoy 0 0 0 0 1 0
## Gilead 0 1 0 0 0 0
## Gilles Plains 0 0 0 94 0 0
## Gillman 0 0 0 4 0 0
## Gilmore 57 0 0 0 0 0
## Giralang 65 0 0 0 0 0
## Girraween 0 97 0 0 0 0
## Girrawheen 0 0 0 0 0 133
## Gladesville 0 328 0 0 0 0
## Gladstone Park 0 0 0 0 158 0
## Gladysdale 0 0 0 0 5 0
## Glandore 0 0 0 61 0 0
## Glanville 0 0 0 26 0 0
## Glebe 0 222 0 0 0 0
## Gledswood Hills 0 212 0 0 0 0
## Glen Alpine 0 55 0 0 0 0
## Glen Forrest 0 0 0 0 0 50
## Glen Huntly 0 0 0 0 157 0
## Glen Iris 0 0 0 0 670 0
## Glen Osmond 0 0 0 57 0 0
## Glen Waverley 0 0 0 0 898 0
## Glenalta 0 0 0 53 0 0
## Glendalough 0 0 0 0 0 45
## Glendenning 0 86 0 0 0 0
## Glenelg 0 0 0 163 0 0
## Glenelg East 0 0 0 141 0 0
## Glenelg North 0 0 0 236 0 0
## Glenelg South 0 0 0 78 0 0
## Glenfield 0 116 0 0 0 0
## Glengowrie 0 0 0 191 0 0
## Glenhaven 0 117 0 0 0 0
## Glenmore Park 0 512 0 0 0 0
## Glenorie 0 39 0 0 0 0
## Glenroy 0 0 0 0 671 0
## Glenside 0 0 0 76 0 0
## Glenunga 0 0 0 65 0 0
## Glenwood 0 264 0 0 0 0
## Globe Derby Park 0 0 0 5 0 0
## Glynde 0 0 0 51 0 0
## Gnangara 0 0 0 0 0 10
## Golden Bay 0 0 0 0 0 140
## Golden Grove 0 0 0 250 0 0
## Goodwood 0 0 0 94 0 0
## Gooseberry Hill 0 0 0 0 0 70
## Gordon 208 207 0 0 0 0
## Gordon Park 0 0 140 0 0 0
## Gosnells 0 0 0 0 0 338
## Gould Creek 0 0 0 2 0 0
## Gowanbrae 0 0 0 0 53 0
## Gowrie 74 0 0 0 0 0
## Graceville 0 0 141 0 0 0
## Grange 0 0 124 164 0 0
## Granville 0 232 0 0 0 0
## Grasmere 0 32 0 0 0 0
## Grays Point 0 52 0 0 0 0
## Great Mackerel Beach 0 4 0 0 0 0
## Green Fields 0 0 0 1 0 0
## Green Valley 0 94 0 0 0 0
## Greenacre 0 277 0 0 0 0
## Greenacres 0 0 0 97 0 0
## Greenfield Park 0 43 0 0 0 0
## Greenhill 0 0 0 14 0 0
## Greenhills Beach 0 21 0 0 0 0
## Greenmount 0 0 0 0 0 69
## Greensborough 0 0 0 0 580 0
## Greenslopes 0 0 299 0 0 0
## Greenvale 0 0 0 0 387 0
## Greenway 128 0 0 0 0 0
## Greenwich 0 117 0 0 0 0
## Greenwith 0 0 0 202 0 0
## Greenwood 0 0 0 0 0 206
## Gregory Hills 0 251 0 0 0 0
## Greystanes 0 326 0 0 0 0
## Griffith 211 0 0 0 0 0
## Gruyere 0 0 0 0 13 0
## Guildford 0 332 0 0 0 53
## Guildford West 0 11 0 0 0 0
## Gulfview Heights 0 0 0 77 0 0
## Gumdale 0 0 48 0 0 0
## Gumeracha 0 0 0 22 0 0
## Gungahlin 257 0 0 0 0 0
## Guys Hill 0 0 0 0 7 0
## Gwelup 0 0 0 0 0 92
## Gymea 0 234 0 0 0 0
## Gymea Bay 0 122 0 0 0 0
## Haberfield 0 96 0 0 0 0
## Hackett 80 0 0 0 0 0
## Hackham 0 0 0 119 0 0
## Hackham West 0 0 0 76 0 0
## Hackney 0 0 0 12 0 0
## Hadfield 0 0 0 0 195 0
## Hall 4 0 0 0 0 0
## Hallam 0 0 0 0 206 0
## Hallett Cove 0 0 0 344 0 0
## Hamersley 0 0 0 0 0 111
## Hamilton 0 0 287 0 0 0
## Hamilton Hill 0 0 0 0 0 256
## Hammond Park 0 0 0 0 0 99
## Hammondville 0 44 0 0 0 0
## Hampstead Gardens 0 0 0 33 0 0
## Hampton 0 0 0 0 396 0
## Hampton East 0 0 0 0 163 0
## Hampton Park 0 0 0 0 520 0
## Happy Valley 0 0 0 274 0 0
## Harkaway 0 0 0 0 14 0
## Harkness 0 0 0 0 368 0
## Harrington Park 0 245 0 0 0 0
## Harris Park 0 95 0 0 0 0
## Harrisdale 0 0 0 0 0 220
## Harrison 172 0 0 0 0 0
## Hassall Grove 0 67 0 0 0 0
## Hastings 0 0 0 0 380 0
## Hawker 56 0 0 0 0 0
## Hawthorn 0 0 0 66 700 0
## Hawthorn East 0 0 0 0 381 0
## Hawthorndene 0 0 0 83 0 0
## Hawthorne 0 0 203 0 0 0
## Haymarket 0 89 0 0 0 0
## Haynes 0 0 0 0 0 30
## Hazelmere 0 0 0 0 0 12
## Hazelwood Park 0 0 0 61 0 0
## Healesville 0 0 0 0 240 0
## Heathcote 0 117 0 0 0 0
## Heatherton 0 0 0 0 54 0
## Heathfield 0 0 0 22 0 0
## Heathmont 0 0 0 0 236 0
## Heathpool 0 0 0 12 0 0
## Heathridge 0 0 0 0 0 171
## Heathwood 0 0 105 0 0 0
## Hebersham 0 70 0 0 0 0
## Heckenberg 0 28 0 0 0 0
## Heidelberg 0 0 0 0 191 0
## Heidelberg Heights 0 0 0 0 229 0
## Heidelberg West 0 0 0 0 150 0
## Helena Valley 0 0 0 0 0 74
## Hemmant 0 0 92 0 0 0
## Hendon 0 0 0 26 0 0
## Hendra 0 0 177 0 0 0
## Henley 0 7 0 0 0 0
## Henley Beach 0 0 0 193 0 0
## Henley Beach South 0 0 0 76 0 0
## Henley Brook 0 0 0 0 0 24
## Herne Hill 0 0 0 0 0 19
## Herston 0 0 69 0 0 0
## Higgins 75 0 0 0 0 0
## High Wycombe 0 0 0 0 0 217
## Highbury 0 0 0 172 0 0
## Highett 0 0 0 0 416 0
## Highgate 0 0 0 38 0 59
## Highgate Hill 0 0 132 0 0 0
## Hilbert 0 0 0 0 0 61
## Hillarys 0 0 0 0 0 242
## Hillbank 0 0 0 127 0 0
## Hillcrest 0 0 0 79 0 0
## Hillier 0 0 0 24 0 0
## Hillman 0 0 0 0 0 38
## Hillsdale 0 120 0 0 0 0
## Hillside 0 0 0 0 319 0
## Hilton 0 0 0 23 0 110
## Hinchinbrook 0 123 0 0 0 0
## Hindmarsh 0 0 0 7 0 0
## Hocking 0 0 0 0 0 130
## Hoddles Creek 0 0 0 0 9 0
## Holden Hill 0 0 0 111 0 0
## Holder 72 0 0 0 0 0
## Holland Park 0 0 208 0 0 0
## Holland Park West 0 0 199 0 0 0
## Holroyd 0 9 0 0 0 0
## Holsworthy 0 59 0 0 0 0
## Holt 159 0 0 0 0 0
## Homebush 0 254 0 0 0 0
## Homebush West 0 205 0 0 0 0
## Hope Valley 0 0 0 177 0 1
## Hopeland 0 0 0 0 0 3
## Hoppers Crossing 0 0 0 0 803 0
## Horningsea Park 0 63 0 0 0 0
## Hornsby 0 506 0 0 0 0
## Hornsby Heights 0 129 0 0 0 0
## Horsley Park 0 5 0 0 0 0
## Houghton 0 0 0 9 0 0
## Hove 0 0 0 92 0 0
## Hovea 0 0 0 0 0 10
## Hoxton Park 0 48 0 0 0 0
## Hughes 67 0 0 0 0 0
## Hughesdale 0 0 0 0 157 0
## Humbug Scrub 0 0 0 2 0 0
## Humevale 0 0 0 0 2 0
## Hunters Hill 0 224 0 0 0 0
## Huntfield Heights 0 0 0 85 0 0
## Huntingdale 0 0 0 0 40 152
## Huntleys Cove 0 23 0 0 0 0
## Huntleys Point 0 1 0 0 0 0
## Hurlstone Park 0 90 0 0 0 0
## Hurstbridge 0 0 0 0 75 0
## Hurstville 0 397 0 0 0 0
## Hurstville Grove 0 38 0 0 0 0
## Hyde Park 0 0 0 49 0 0
## Illawong 0 122 0 0 0 0
## Iluka 0 0 0 0 0 120
## Inala 0 0 175 0 0 0
## Indooroopilly 0 0 363 0 0 0
## Ingle Farm 0 0 0 239 0 0
## Ingleburn 0 227 0 0 0 0
## Ingleside 0 7 0 0 0 0
## Inglewood 0 0 0 3 0 135
## Innaloo 0 0 0 0 0 193
## Iona 0 0 0 0 1 0
## Ironbank 0 0 0 10 0 0
## Isaacs 65 0 0 0 0 0
## Isabella Plains 107 0 0 0 0 0
## Ivanhoe 0 0 0 0 316 0
## Ivanhoe East 0 0 0 0 94 0
## Jacana 0 0 0 0 56 0
## Jacka 13 0 0 0 0 0
## Jamboree Heights 0 0 65 0 0 0
## Jamisontown 0 127 0 0 0 0
## Jandabup 0 0 0 0 0 1
## Jandakot 0 0 0 0 0 47
## Jane Brook 0 0 0 0 0 79
## Jannali 0 150 0 0 0 0
## Jarrahdale 0 0 0 0 0 24
## Jindalee 0 0 151 0 0 85
## Jolimont 0 0 0 0 0 30
## Joondalup 0 0 0 0 0 208
## Joondanna 0 0 0 0 0 132
## Jordan Springs 0 267 0 0 0 0
## Joslin 0 0 0 24 0 0
## Junction Village 0 0 0 0 23 0
## Kalamunda 0 0 0 0 0 161
## Kaleen 138 0 0 0 0 0
## Kalkallo 0 0 0 0 143 0
## Kallaroo 0 0 0 0 0 120
## Kallista 0 0 0 0 34 0
## Kalorama 0 0 0 0 45 0
## Kambah 347 0 0 0 0 0
## Kangarilla 0 0 0 11 0 0
## Kangaroo Ground 0 0 0 0 19 0
## Kangaroo Point 0 6 320 0 0 0
## Karana Downs 0 0 106 0 0 0
## Karawara 0 0 0 0 0 18
## Kardinya 0 0 0 0 0 174
## Kareela 0 66 0 0 0 0
## Karnup 0 0 0 0 0 18
## Karragullen 0 0 0 0 0 5
## Karrakup 0 0 0 0 0 2
## Karrinyup 0 0 0 0 0 202
## Kealba 0 0 0 0 45 0
## Kearns 0 49 0 0 0 0
## Kedron 0 0 320 0 0 0
## Keilor 0 0 0 0 107 0
## Keilor Downs 0 0 0 0 132 0
## Keilor East 0 0 0 0 346 0
## Keilor Lodge 0 0 0 0 2 0
## Keilor North 0 0 0 0 1 0
## Keilor Park 0 0 0 0 34 0
## Kellyville 0 659 0 0 0 0
## Kellyville Ridge 0 231 0 0 0 0
## Kelmscott 0 0 0 0 0 193
## Kelvin Grove 0 0 188 0 0 0
## Kemps Creek 0 9 0 0 0 0
## Kenmore 0 0 290 0 0 0
## Kenmore Hills 0 0 46 0 0 0
## Kensington 0 195 0 50 368 83
## Kensington Gardens 0 0 0 123 0 0
## Kensington Park 0 0 0 60 0 0
## Kent Town 0 0 0 31 0 0
## Kenthurst 0 60 0 0 0 0
## Kentlyn 0 1 0 0 0 0
## Kenton Valley 0 0 0 1 0 0
## Kenwick 0 0 0 0 0 74
## Keperra 0 0 176 0 0 0
## Kersbrook 0 0 0 12 0 0
## Keswick 0 0 0 11 0 0
## Kew 0 0 0 0 623 0
## Kew East 0 0 0 0 146 0
## Kewdale 0 0 0 0 0 125
## Keysborough 0 0 0 0 584 0
## Keysbrook 0 0 0 0 0 2
## Kholo 0 0 3 0 0 0
## Kiara 0 0 0 0 0 28
## Kidman Park 0 0 0 58 0 0
## Kilburn 0 0 0 82 0 0
## Kilkenny 0 0 0 33 0 0
## Killara 0 256 0 0 0 0
## Killarney Heights 0 77 0 0 0 0
## Kilsyth 0 0 0 0 392 0
## Kilsyth South 0 0 0 0 42 0
## Kings Langley 0 175 0 0 0 0
## Kings Park 0 79 0 12 122 0
## Kingsbury 0 0 0 0 66 0
## Kingsford 0 193 0 0 0 0
## Kingsgrove 0 187 0 0 0 0
## Kingsley 0 0 0 0 0 256
## Kingston 256 0 0 0 0 0
## Kingston Park 0 0 0 14 0 0
## Kingsville 0 0 0 0 131 0
## Kingswood 0 247 0 68 0 0
## Kinross 0 0 0 0 0 137
## Kirkham 0 11 0 0 0 0
## Kirrawee 0 241 0 0 0 0
## Kirribilli 0 85 0 0 0 0
## Klemzig 0 0 0 177 0 0
## Knoxfield 0 0 0 0 185 0
## Kogarah 0 255 0 0 0 0
## Kogarah Bay 0 38 0 0 0 0
## Koo Wee Rup 0 0 0 0 98 0
## Koondoola 0 0 0 0 0 44
## Koongamia 0 0 0 0 0 19
## Kooyong 0 0 0 0 18 0
## Kudla 0 0 0 5 0 0
## Kuraby 0 0 141 0 0 0
## Kurnell 0 37 0 0 0 0
## Kurraba Point 0 18 0 0 0 0
## Kurralta Park 0 0 0 123 0 0
## Kurunjang 0 0 0 0 285 0
## Kwinana Town Centre 0 0 0 0 0 15
## Kyeemagh 0 13 0 0 0 0
## Kyle Bay 0 18 0 0 0 0
## La Perouse 0 4 0 0 0 0
## Lakemba 0 227 0 0 0 0
## Lalor 0 0 0 0 393 0
## Lalor Park 0 182 0 0 0 0
## Landsdale 0 0 0 0 0 222
## Lane Cove 0 733 0 0 0 0
## Lane Cove North 0 74 0 0 0 0
## Lane Cove West 0 7 0 0 0 0
## Lang Lang East 0 0 0 0 2 0
## Langford 0 0 0 0 0 65
## Langwarrin 0 0 0 0 682 0
## Langwarrin South 0 0 0 0 12 0
## Lansvale 0 28 0 0 0 0
## Largs Bay 0 0 0 111 0 0
## Largs North 0 0 0 107 0 0
## Latham 76 0 0 0 0 0
## Lathlain 0 0 0 0 0 83
## Launching Place 0 0 0 0 64 0
## Lavender Bay 0 22 0 0 0 0
## Laverton 0 0 0 0 188 0
## Lawson 59 0 0 0 0 0
## Leabrook 0 0 0 42 0 0
## Leawood Gardens 0 0 0 2 0 0
## Leda 0 0 0 0 0 56
## Leederville 0 0 0 0 0 97
## Leeming 0 0 0 0 0 193
## Leichhardt 0 437 0 0 0 0
## Lenswood 0 0 0 7 0 0
## Leonay 0 55 0 0 0 0
## Leppington 0 135 0 0 0 0
## Lesmurdie 0 0 0 0 0 135
## Lethbridge Park 0 77 0 0 0 0
## Leumeah 0 179 0 0 0 0
## Lewisham 0 97 0 0 0 0
## Lewiston 0 0 0 64 0 0
## Lexia 0 0 0 0 0 1
## Liberty Grove 0 36 0 0 0 0
## Lidcombe 0 219 0 0 0 0
## Lightsview 0 0 0 232 0 0
## Lilli Pilli 0 29 0 0 0 0
## Lilydale 0 0 0 0 472 0
## Lilyfield 0 195 0 0 0 0
## Linden Park 0 0 0 69 0 0
## Lindfield 0 241 0 0 0 0
## Linley Point 0 3 0 0 0 0
## Little Bay 0 89 0 0 0 0
## Liverpool 0 541 0 0 0 0
## Llandilo 0 25 0 0 0 0
## Lobethal 0 0 0 58 0 0
## Lockleys 0 0 0 138 0 0
## Lockridge 0 0 0 0 0 52
## Loftus 0 61 0 0 0 0
## Londonderry 0 24 0 0 0 0
## Longueville 0 32 0 0 0 0
## Longwood 0 0 0 4 0 0
## Lota 0 0 99 0 0 0
## Lovett Bay 0 5 0 0 0 0
## Lower Hermitage 0 0 0 4 0 0
## Lower Mitcham 0 0 0 64 0 0
## Lower Plenty 0 0 0 0 116 0
## Luddenham 0 13 0 0 0 0
## Lugarno 0 115 0 0 0 0
## Lurnea 0 125 0 0 0 0
## Lutwyche 0 0 117 0 0 0
## Lynbrook 0 0 0 0 127 0
## Lyndhurst 0 0 0 0 181 0
## Lyneham 145 0 0 0 0 0
## Lynton 0 0 0 6 0 0
## Lynwood 0 0 0 0 0 89
## Lyons 86 0 0 0 0 0
## Lysterfield 0 0 0 0 103 0
## Lysterfield South 0 0 0 0 9 0
## Macarthur 24 0 0 0 0 0
## Macclesfield 0 0 0 0 13 0
## Macdonald Park 0 0 0 3 0 0
## MacGregor 186 0 98 0 0 0
## Macleod 0 0 0 0 252 0
## Macquarie 80 0 0 0 0 0
## Macquarie Fields 0 153 0 0 0 0
## Macquarie Links 0 18 0 0 0 0
## Macquarie Park 0 193 0 0 0 0
## Maddington 0 0 0 0 0 174
## Madeley 0 0 0 0 0 112
## Magill 0 0 0 287 0 0
## Mahogany Creek 0 0 0 0 0 19
## Maianbar 0 10 0 0 0 0
## Maida Vale 0 0 0 0 0 88
## Maidstone 0 0 0 0 268 0
## Main Ridge 0 0 0 0 13 0
## Malabar 0 47 0 0 0 0
## Mallala 0 0 0 23 0 0
## Malvern 0 0 0 71 272 0
## Malvern East 0 0 0 0 529 0
## Mambourin 0 0 0 0 1 0
## Manly 0 539 113 0 0 0
## Manly Vale 0 169 0 0 0 0
## Manly West 0 0 333 0 0 0
## Manning 0 0 0 0 0 113
## Manningham 0 0 0 31 0 0
## Manor Lakes 0 0 0 0 243 0
## Mansfield 0 0 217 0 0 0
## Mansfield Park 0 0 0 65 0 0
## Marangaroo 0 0 0 0 0 144
## Marayong 0 130 0 0 0 0
## Marble Hill 0 0 0 1 0 0
## Mardella 0 0 0 0 0 5
## Marden 0 0 0 81 0 0
## Maribyrnong 0 0 0 0 349 0
## Mariginiup 0 0 0 0 0 3
## Marino 0 0 0 48 0 0
## Marion 0 0 0 122 0 0
## Marleston 0 0 0 65 0 0
## Marmion 0 0 0 0 0 35
## Maroubra 0 483 0 0 0 0
## Marrickville 0 553 0 0 0 0
## Marryatville 0 0 0 24 0 0
## Marsden Park 0 375 0 0 0 0
## Marsfield 0 221 0 0 0 0
## Martin 0 0 0 0 0 22
## Maryknoll 0 0 0 0 4 0
## Mascot 0 271 0 0 0 0
## Maslin Beach 0 0 0 35 0 0
## Matraville 0 138 0 0 0 0
## Mawson 130 0 0 0 0 0
## Mawson Lakes 0 0 0 447 0 0
## Maylands 0 0 0 41 0 362
## Mays Hill 0 15 0 0 0 0
## McCrae 0 0 0 0 138 0
## McDowall 0 0 154 0 0 0
## McKellar 41 0 0 0 0 0
## McKinnon 0 0 0 0 124 0
## McLaren Flat 0 0 0 37 0 0
## McLaren Vale 0 0 0 102 0 0
## McMahons Creek 0 0 0 0 8 0
## McMahons Point 0 92 0 0 0 0
## Meadow Heights 0 0 0 0 226 0
## Meadowbank 0 158 0 0 0 0
## Medina 0 0 0 0 0 54
## Medindie 0 0 0 23 0 0
## Medindie Gardens 0 0 0 14 0 0
## Melba 81 0 0 0 0 0
## Melbourne 0 0 0 0 1401 0
## Melrose Park 0 15 0 72 0 0
## Melton 0 0 0 0 312 0
## Melton South 0 0 0 0 448 0
## Melton West 0 0 0 0 301 0
## Melville 0 0 0 0 0 167
## Menai 0 246 0 0 0 0
## Menangle Park 0 2 0 0 0 0
## Menora 0 0 0 0 0 27
## Mentone 0 0 0 0 367 0
## Menzies Creek 0 0 0 0 19 0
## Mernda 0 0 0 0 614 0
## Merricks 0 0 0 0 3 0
## Merricks Beach 0 0 0 0 5 0
## Merricks North 0 0 0 0 10 0
## Merriwa 0 0 0 0 0 95
## Merrylands 0 495 0 0 0 0
## Merrylands West 0 23 0 0 0 0
## Mickleham 0 0 0 0 466 0
## Middle Cove 0 21 0 0 0 0
## Middle Dural 0 8 0 0 0 0
## Middle Park 0 0 90 0 105 0
## Middle Swan 0 0 0 0 0 45
## Middleton Grange 0 108 0 0 0 0
## Midland 0 0 0 0 0 103
## Midvale 0 0 0 0 0 36
## Mile End 0 0 0 98 0 0
## Mill Park 0 0 0 0 518 0
## Millendon 0 0 0 0 0 6
## Miller 0 32 0 0 0 0
## Millers Point 0 12 0 0 0 0
## Millgrove 0 0 0 0 75 0
## Millswood 0 0 0 52 0 0
## Milperra 0 77 0 0 0 0
## Milsons Passage 0 1 0 0 0 0
## Milsons Point 0 69 0 0 0 0
## Milton 0 0 71 0 0 0
## Minchinbury 0 83 0 0 0 0
## Mindarie 0 0 0 0 0 171
## Minto 0 151 0 0 0 0
## Minto Heights 0 1 0 0 0 0
## Miranda 0 405 0 0 0 0
## Mirrabooka 0 0 0 0 0 98
## Mitcham 0 0 0 73 452 0
## Mitchell Park 0 0 0 146 0 0
## Mitchelton 0 0 230 0 0 0
## Moana 0 0 0 79 0 0
## Modbury 0 0 0 150 0 0
## Modbury Heights 0 0 0 172 0 0
## Modbury North 0 0 0 116 0 0
## Moggill 0 0 148 0 0 0
## Mona Vale 0 273 0 0 0 0
## Monash 113 0 0 0 0 0
## Monbulk 0 0 0 0 89 0
## Moncrieff 124 0 0 0 0 0
## Monomeith 0 0 0 0 1 0
## Mont Albert 0 0 0 0 105 0
## Mont Albert North 0 0 0 0 148 0
## Montacute 0 0 0 4 0 0
## Monterey 0 72 0 0 0 0
## Montmorency 0 0 0 0 248 0
## Montrose 0 0 0 0 139 0
## Moonee Ponds 0 0 0 0 371 0
## Moorabbin 0 0 0 0 193 0
## Moorebank 0 212 0 0 0 0
## Moorooduc 0 0 0 0 4 0
## Moorooka 0 0 330 0 0 0
## Mooroolbark 0 0 0 0 588 0
## Mordialloc 0 0 0 0 274 0
## Morley 0 0 0 0 0 441
## Morningside 0 0 455 0 0 0
## Mornington 0 0 0 0 928 0
## Morphett Vale 0 0 0 640 0 0
## Morphettville 0 0 0 113 0 0
## Mortdale 0 212 0 0 0 0
## Mortlake 0 44 0 0 0 0
## Mosman 0 745 0 0 0 0
## Mosman Park 0 0 0 0 0 208
## Mount Annan 0 252 0 0 0 0
## Mount Burnett 0 0 0 0 5 0
## Mount Claremont 0 0 0 0 0 139
## Mount Colah 0 161 0 0 0 0
## Mount Cottrell 0 0 0 0 1 0
## Mount Crosby 0 0 24 0 0 0
## Mount Dandenong 0 0 0 0 38 0
## Mount Druitt 0 228 0 0 0 0
## Mount Eliza 0 0 0 0 560 0
## Mount Evelyn 0 0 0 0 225 0
## Mount George 0 0 0 7 0 0
## Mount Gravatt 0 0 98 0 0 0
## Mount Gravatt East 0 0 356 0 0 0
## Mount Hawthorn 0 0 0 0 0 174
## Mount Helena 0 0 0 0 0 65
## Mount Kuring-Gai 0 32 0 0 0 0
## Mount Lawley 0 0 0 0 0 291
## Mount Lewis 0 11 0 0 0 0
## Mount Martha 0 0 0 0 655 0
## Mount Nasura 0 0 0 0 0 63
## Mount Ommaney 0 0 37 0 0 0
## Mount Osmond 0 0 0 17 0 0
## Mount Pleasant 0 0 0 0 0 208
## Mount Pritchard 0 131 0 0 0 0
## Mount Richon 0 0 0 0 0 45
## Mount Toolebewong 0 0 0 0 1 0
## Mount Vernon 0 9 0 0 0 0
## Mount Waverley 0 0 0 0 902 0
## Mulgoa 0 15 0 0 0 0
## Mulgrave 0 0 0 0 396 0
## Mullaloo 0 0 0 0 0 142
## Mundaring 0 0 0 0 0 85
## Mundijong 0 0 0 0 0 31
## Munno Para 0 0 0 99 0 0
## Munno Para West 0 0 0 210 0 0
## Munster 0 0 0 0 0 99
## Murarrie 0 0 155 0 0 0
## Murdoch 0 0 0 0 0 28
## Murrumbeena 0 0 0 0 258 0
## Myaree 0 0 0 0 0 68
## Mylor 0 0 0 11 0 0
## Myrtle Bank 0 0 0 79 0 0
## Nailsworth 0 0 0 48 0 0
## Nar Nar Goon 0 0 0 0 13 0
## Nar Nar Goon North 0 0 0 0 7 0
## Narellan 0 66 0 0 0 0
## Narellan Vale 0 155 0 0 0 0
## Naremburn 0 157 0 0 0 0
## Narrabeen 0 272 0 0 0 0
## Narrabundah 178 0 0 0 0 0
## Narraweena 0 93 0 0 0 0
## Narre Warren 0 0 0 0 608 0
## Narre Warren East 0 0 0 0 6 0
## Narre Warren North 0 0 0 0 88 0
## Narre Warren South 0 0 0 0 597 0
## Narwee 0 65 0 0 0 0
## Nathan 0 0 13 0 0 0
## Nedlands 0 0 0 0 0 243
## Netherby 0 0 0 56 0 0
## Netley 0 0 0 38 0 0
## Neutral Bay 0 375 0 0 0 0
## New Farm 0 0 434 0 0 0
## New Port 0 0 0 37 0 0
## Newington 0 91 0 0 0 0
## Newmarket 0 0 122 0 0 0
## Newport 0 280 0 0 398 0
## Newstead 0 0 217 0 0 0
## Newtown 0 368 0 0 0 0
## Ngunnawal 323 0 0 0 0 0
## Nicholls 142 0 0 0 0 0
## Niddrie 0 0 0 0 161 0
## Noarlunga Centre 0 0 0 8 0 0
## Noarlunga Downs 0 0 0 96 0 0
## Noble Park 0 0 0 0 634 0
## Noble Park North 0 0 0 0 92 0
## Nollamara 0 0 0 0 0 165
## Noranda 0 0 0 0 0 121
## Norman Park 0 0 213 0 0 0
## Normanhurst 0 87 0 0 0 0
## North Adelaide 0 0 0 217 0 0
## North Balgowlah 0 87 0 0 0 0
## North Beach 0 0 0 0 0 84
## North Bondi 0 236 0 0 0 0
## North Brighton 0 0 0 51 0 0
## North Coogee 0 0 0 0 0 108
## North Curl Curl 0 72 0 0 0 0
## North Epping 0 69 0 0 0 0
## North Fremantle 0 0 0 0 0 126
## North Haven 0 0 0 132 0 0
## North Kellyville 0 237 0 0 0 0
## North Lake 0 0 0 0 0 26
## North Manly 0 62 0 0 0 0
## North Melbourne 0 0 0 0 368 0
## North Narrabeen 0 90 0 0 0 0
## North Parramatta 0 224 0 0 0 0
## North Perth 0 0 0 0 0 256
## North Plympton 0 0 0 101 0 0
## North Rocks 0 142 0 0 0 0
## North Ryde 0 228 0 0 0 0
## North St Marys 0 54 0 0 0 0
## North Strathfield 0 92 0 0 0 0
## North Sydney 0 218 0 0 0 0
## North Turramurra 0 20 0 0 0 0
## North Wahroonga 0 1 0 0 0 0
## North Warrandyte 0 0 0 0 69 0
## North Willoughby 0 6 0 0 0 0
## Northbridge 0 133 0 0 0 45
## Northcote 0 0 0 0 670 0
## Northfield 0 0 0 106 0 0
## Northgate 0 0 142 86 0 0
## Northmead 0 218 0 0 0 0
## Northwood 0 20 0 0 0 0
## Norton Summit 0 0 0 8 0 0
## Norwest 0 63 0 0 0 0
## Norwood 0 0 0 214 0 0
## Notting Hill 0 0 0 0 84 0
## Novar Gardens 0 0 0 53 0 0
## Nowergup 0 0 0 0 0 2
## Nudgee 0 0 110 0 0 0
## Nudgee Beach 0 0 11 0 0 0
## Nunawading 0 0 0 0 277 0
## Nundah 0 0 468 0 0 0
## O'Connor 135 0 0 0 0 14
## O'Halloran Hill 0 0 0 79 0 0
## O'Malley 18 0 0 0 0 0
## O'Sullivan Beach 0 0 0 47 0 0
## Oak Park 0 0 0 0 211 0
## Oakbank 0 0 0 19 0 0
## Oakden 0 0 0 79 0 0
## Oakford 0 0 0 0 0 24
## Oakhurst 0 97 0 0 0 0
## Oaklands Junction 0 0 0 0 3 0
## Oaklands Park 0 0 0 131 0 0
## Oakleigh 0 0 0 0 152 0
## Oakleigh East 0 0 0 0 146 0
## Oakleigh South 0 0 0 0 208 0
## Oaks Estate 3 0 0 0 0 0
## Oatlands 0 80 0 0 0 0
## Oatley 0 180 0 0 0 0
## Ocean Reef 0 0 0 0 0 131
## Officer 0 0 0 0 533 0
## Officer South 0 0 0 0 3 0
## Old Guildford 0 7 0 0 0 0
## Old Noarlunga 0 0 0 42 0 0
## Old Reynella 0 0 0 81 0 0
## Old Toongabbie 0 51 0 0 0 0
## Olinda 0 0 0 0 46 0
## One Tree Hill 0 0 0 18 0 0
## Onkaparinga Hills 0 0 0 50 0 0
## Oran Park 0 419 0 0 0 0
## Orange Grove 0 0 0 0 0 2
## Orchard Hills 0 7 0 0 0 0
## Orelia 0 0 0 0 0 93
## Ormond 0 0 0 0 215 0
## Osborne 0 0 0 54 0 0
## Osborne Park 0 0 0 0 0 57
## Ottoway 0 0 0 43 0 0
## Ovingham 0 0 0 18 0 0
## Oxley 35 0 269 0 0 0
## Oxley Park 0 136 0 0 0 0
## Oyster Bay 0 130 0 0 0 0
## Padbury 0 0 0 0 0 204
## Paddington 0 371 317 0 0 0
## Padstow 0 184 0 0 0 0
## Padstow Heights 0 55 0 0 0 0
## Page 71 0 0 0 0 0
## Pagewood 0 62 0 0 0 0
## Pakenham 0 0 0 0 1818 0
## Pakenham South 0 0 0 0 2 0
## Pakenham Upper 0 0 0 0 10 0
## Pallara 0 0 42 0 0 0
## Palm Beach 0 87 0 0 0 0
## Palmerston 132 0 0 0 0 0
## Palmyra 0 0 0 0 0 255
## Panania 0 166 0 0 0 0
## Panorama 0 0 0 67 0 0
## Panton Hill 0 0 0 0 10 0
## Para Hills 0 0 0 181 0 0
## Para Hills West 0 0 0 86 0 0
## Para Vista 0 0 0 57 0 0
## Paracombe 0 0 0 6 0 0
## Parafield Gardens 0 0 0 297 0 0
## Paralowie 0 0 0 283 0 0
## Park Holme 0 0 0 111 0 0
## Park Orchards 0 0 0 0 53 0
## Parkdale 0 0 0 0 353 0
## Parkerville 0 0 0 0 0 45
## Parkinson 0 0 264 0 0 0
## Parklea 0 39 0 0 0 0
## Parkside 0 0 0 130 0 0
## Parkville 0 0 0 0 100 0
## Parkwood 0 0 0 0 0 109
## Parmelia 0 0 0 0 0 121
## Parramatta 0 547 0 0 0 0
## Pasadena 0 0 0 70 0 0
## Pascoe Vale 0 0 0 0 553 0
## Pascoe Vale South 0 0 0 0 214 0
## Patterson Lakes 0 0 0 0 233 0
## Payneham 0 0 0 84 0 0
## Payneham South 0 0 0 53 0 0
## Peakhurst 0 190 0 0 0 0
## Peakhurst Heights 0 39 0 0 0 0
## Pearce 67 0 0 0 0 0
## Pearcedale 0 0 0 0 74 0
## Pearsall 0 0 0 0 0 83
## Pemulwuy 0 80 0 0 0 0
## Pendle Hill 0 104 0 0 0 0
## Penfield 0 0 0 26 0 0
## Penfield Gardens 0 0 0 2 0 0
## Pennant Hills 0 135 0 0 0 0
## Pennington 0 0 0 69 0 0
## Penrith 0 439 0 0 0 0
## Penshurst 0 182 0 0 0 0
## Peppermint Grove 0 0 0 0 0 24
## Perth 0 0 0 0 0 349
## Peterhead 0 0 0 35 0 0
## Petersham 0 184 0 0 0 0
## Petrie Terrace 0 0 35 0 0 0
## Phillip 153 0 0 0 0 0
## Phillip Bay 0 7 0 0 0 0
## Piara Waters 0 0 0 0 0 241
## Piccadilly 0 0 0 9 0 0
## Pickering Brook 0 0 0 0 0 4
## Picnic Point 0 101 0 0 0 0
## Piesse Brook 0 0 0 0 0 3
## Pinjarra Hills 0 0 5 0 0 0
## Pinkenba 0 0 3 0 0 0
## Pleasure Point 0 6 0 0 0 0
## Plenty 0 0 0 0 34 0
## Plumpton 0 123 0 0 38 0
## Plympton 0 0 0 205 0 0
## Plympton Park 0 0 0 95 0 0
## Point Cook 0 0 0 0 1440 0
## Point Leo 0 0 0 0 1 0
## Point Piper 0 30 0 0 0 0
## Pooraka 0 0 0 141 0 0
## Port Adelaide 0 0 0 42 0 0
## Port Hacking 0 17 0 0 0 0
## Port Kennedy 0 0 0 0 0 270
## Port Melbourne 0 0 0 0 606 0
## Port Noarlunga 0 0 0 92 0 0
## Port Noarlunga South 0 0 0 80 0 0
## Port Willunga 0 0 0 60 0 0
## Portsea 0 0 0 0 79 0
## Potts Hill 0 9 0 0 0 0
## Potts Point 0 282 0 0 0 0
## Powelltown 0 0 0 0 8 0
## Prahran 0 0 0 0 606 0
## Prairiewood 0 25 0 0 0 0
## Preston 0 0 0 0 864 0
## Prestons 0 161 0 0 0 0
## Princes Hill 0 0 0 0 2 0
## Prospect 0 78 0 381 0 0
## Pullenvale 0 0 31 0 0 0
## Punchbowl 0 222 0 0 0 0
## Putney 0 67 0 0 0 0
## Pymble 0 259 0 0 0 0
## Pyrmont 0 246 0 0 0 0
## Quakers Hill 0 497 0 0 0 0
## Queens Park 0 85 0 0 0 96
## Queenscliff 0 156 0 0 0 0
## Queenstown 0 0 0 55 0 0
## Quinns Rocks 0 0 0 0 0 216
## Raby 0 119 0 0 0 0
## Ramsgate 0 31 0 0 0 0
## Ramsgate Beach 0 30 0 0 0 0
## Randwick 0 624 0 0 0 0
## Ransome 0 0 3 0 0 0
## Red Hill 66 0 175 0 40 0
## Red Hill South 0 0 0 0 6 0
## Redcliffe 0 0 0 0 0 71
## Redfern 0 258 0 0 0 0
## Redwood Park 0 0 0 132 0 0
## Reefton 0 0 0 0 3 0
## Regents Park 0 51 0 0 0 0
## Regentville 0 16 0 0 0 0
## Reid 43 0 0 0 0 0
## Renown Park 0 0 0 40 0 0
## Research 0 0 0 0 65 0
## Reservoir 0 0 0 0 1199 0
## Revesby 0 188 0 0 0 0
## Revesby Heights 0 33 0 0 0 0
## Reynella 0 0 0 156 0 0
## Reynella East 0 0 0 39 0 0
## Rhodes 0 281 0 0 0 0
## Richardson 61 0 0 0 0 0
## Richlands 0 0 72 0 0 0
## Richmond 0 0 0 86 950 0
## Ridgehaven 0 0 0 103 0 0
## Ridgewood 0 0 0 0 0 73
## Ridleyton 0 0 0 27 0 0
## Ringwood 0 0 0 0 553 0
## Ringwood East 0 0 0 0 324 0
## Ringwood North 0 0 0 0 207 0
## Ripponlea 0 0 0 0 37 0
## Riverhills 0 0 103 0 0 0
## Riverstone 0 319 0 0 0 0
## Riverton 0 0 0 0 0 111
## Rivervale 0 0 0 0 0 261
## Riverview 0 57 0 0 0 0
## Riverwood 0 153 0 0 0 0
## Rivett 60 0 0 0 0 0
## Robertson 0 0 53 0 0 0
## Rochedale 0 0 147 0 0 0
## Rockbank 0 0 0 0 58 0
## Rockdale 0 238 0 0 0 0
## Rockingham 0 0 0 0 0 380
## Rocklea 0 0 56 0 0 0
## Rodd Point 0 16 0 0 0 0
## Roleystone 0 0 0 0 0 145
## Rooty Hill 0 206 0 0 0 0
## Ropes Crossing 0 142 0 0 0 0
## Rosanna 0 0 0 0 220 0
## Rose Bay 0 304 0 0 0 0
## Rose Park 0 0 0 36 0 0
## Rosebery 0 271 0 0 0 0
## Rosebud 0 0 0 0 698 0
## Rosehill 0 59 0 0 0 0
## Roselands 0 175 0 0 0 0
## Rosemeadow 0 100 0 0 0 0
## Roseville 0 241 0 0 0 0
## Roseville Chase 0 26 0 0 0 0
## Rosewater 0 0 0 104 0 0
## Rosslyn Park 0 0 0 27 0 0
## Rossmore 0 12 0 0 0 0
## Rossmoyne 0 0 0 0 0 56
## Rostrevor 0 0 0 229 0 0
## Rouse Hill 0 221 0 0 0 0
## Rowville 0 0 0 0 609 0
## Roxburgh Park 0 0 0 0 418 0
## Royal Park 0 0 0 90 0 0
## Royston Park 0 0 0 32 0 0
## Rozelle 0 263 0 0 0 0
## Runcorn 0 0 280 0 0 0
## Ruse 0 126 0 0 0 0
## Rushcutters Bay 0 72 0 0 0 0
## Russell Lea 0 94 0 0 0 0
## Rydalmere 0 119 0 0 0 0
## Ryde 0 614 0 0 0 0
## Rye 0 0 0 0 589 0
## Rythdale 0 0 0 0 1 0
## Sackville North 0 2 0 0 0 0
## Sadleir 0 36 0 0 0 0
## Safety Bay 0 0 0 0 0 200
## Safety Beach 0 0 0 0 298 0
## Salisbury 0 0 180 187 0 0
## Salisbury Downs 0 0 0 125 0 0
## Salisbury East 0 0 0 190 0 0
## Salisbury Heights 0 0 0 111 0 0
## Salisbury North 0 0 0 200 0 0
## Salisbury Park 0 0 0 35 0 0
## Salisbury Plain 0 0 0 29 0 0
## Salter Point 0 0 0 0 0 43
## Samson 0 0 0 0 0 49
## Sandgate 0 0 128 0 0 0
## Sandhurst 0 0 0 0 147 0
## Sandringham 0 29 0 0 327 0
## Sandy Point 0 8 0 0 0 0
## Sans Souci 0 191 0 0 0 0
## Sassafras 0 0 0 0 24 0
## Sawyers Valley 0 0 0 0 0 19
## Scarborough 0 0 0 0 0 479
## Schofields 0 459 0 0 0 0
## Scoresby 0 0 0 0 114 0
## Scotland Island 0 15 0 0 0 0
## Scott Creek 0 0 0 5 0 0
## Scullin 69 0 0 0 0 0
## Seabrook 0 0 0 0 111 0
## Seacliff 0 0 0 58 0 0
## Seacliff Park 0 0 0 91 0 0
## Seacombe Gardens 0 0 0 139 0 0
## Seacombe Heights 0 0 0 50 0 0
## Seaford 0 0 0 110 591 0
## Seaford Heights 0 0 0 20 0 0
## Seaford Meadows 0 0 0 145 0 0
## Seaford Rise 0 0 0 156 0 0
## Seaforth 0 185 0 0 0 0
## Seaholme 0 0 0 0 46 0
## Seaton 0 0 0 290 0 0
## Seaview Downs 0 0 0 62 0 0
## Secret Harbour 0 0 0 0 0 292
## Seddon 0 0 0 0 164 0
## Sefton 0 60 0 0 0 0
## Sefton Park 0 0 0 40 0 0
## Selby 0 0 0 0 38 0
## Sellicks Beach 0 0 0 120 0 0
## Semaphore 0 0 0 81 0 0
## Semaphore Park 0 0 0 108 0 0
## Semaphore South 0 0 0 31 0 0
## Serpentine 0 0 0 0 0 35
## Seven Hills 0 327 80 0 0 0
## Seventeen Mile Rocks 0 0 59 0 0 0
## Seville 0 0 0 0 52 0
## Seville East 0 0 0 0 25 0
## Seville Grove 0 0 0 0 0 177
## Shalvey 0 37 0 0 0 0
## Sheidow Park 0 0 0 151 0 0
## Shelley 0 0 0 0 0 90
## Shenton Park 0 0 0 0 0 114
## Sherbrooke 0 0 0 0 8 0
## Sherwood 0 0 207 0 0 0
## Shoalwater 0 0 0 0 0 110
## Shoreham 0 0 0 0 20 0
## Shorncliffe 0 0 35 0 0 0
## Silvan 0 0 0 0 24 0
## Silverwater 0 42 0 0 0 0
## Sinagra 0 0 0 0 0 60
## Singleton 0 0 0 0 0 88
## Sinnamon Park 0 0 148 0 0 0
## Skye 0 0 0 7 221 0
## Smithfield 0 123 0 75 0 0
## Smithfield Plains 0 0 0 67 0 0
## Smiths Gully 0 0 0 0 8 0
## Somers 0 0 0 0 80 0
## Somerton Park 0 0 0 188 0 0
## Somerville 0 0 0 0 302 0
## Sorrento 0 0 0 0 180 198
## South Brighton 0 0 0 70 0 0
## South Brisbane 0 0 351 0 0 0
## South Coogee 0 68 0 0 0 0
## South Fremantle 0 0 0 0 0 91
## South Granville 0 9 0 0 0 0
## South Guildford 0 0 0 0 0 78
## South Hurstville 0 87 0 0 0 0
## South Kingsville 0 0 0 0 88 0
## South Lake 0 0 0 0 0 116
## South Maroota 0 2 0 0 0 0
## South Melbourne 0 0 0 0 387 0
## South Morang 0 0 0 0 497 0
## South Penrith 0 230 0 0 0 0
## South Perth 0 0 0 0 0 366
## South Plympton 0 0 0 143 0 0
## South Turramurra 0 2 0 0 0 0
## South Wentworthville 0 84 0 0 0 0
## South Yarra 0 0 0 0 892 0
## Southbank 0 0 0 0 838 0
## Southern River 0 0 0 0 0 179
## Spearwood 0 0 0 0 0 242
## Spence 44 0 0 0 0 0
## Spotswood 0 0 0 0 79 0
## Spring Farm 0 300 0 0 0 0
## Spring Hill 0 0 157 0 0 0
## Springfield 0 0 0 15 0 0
## Springvale 0 0 0 0 259 0
## Springvale South 0 0 0 0 146 0
## St Agnes 0 0 0 103 0 0
## St Albans 0 0 0 0 621 0
## St Andrews 0 94 0 0 21 0
## St Andrews Beach 0 0 0 0 39 0
## St Clair 0 318 0 95 0 0
## St Georges 0 0 0 66 0 0
## St Helena 0 0 0 0 59 0
## St Helens Park 0 112 0 0 0 0
## St Ives 0 566 0 0 0 0
## St Ives Chase 0 6 0 0 0 0
## St James 0 0 0 0 0 115
## St Johns Park 0 44 0 0 0 0
## St Kilda 0 0 0 2 825 0
## St Kilda East 0 0 0 0 484 0
## St Kilda West 0 0 0 0 98 0
## St Leonards 0 245 0 0 0 0
## St Lucia 0 0 326 0 0 0
## St Marys 0 305 0 98 0 0
## St Morris 0 0 0 27 0 0
## St Peters 0 79 0 77 0 0
## Stafford 0 0 254 0 0 0
## Stafford Heights 0 0 201 0 0 0
## Stanhope Gardens 0 205 0 0 0 0
## Stanmore 0 179 0 0 0 0
## Steels Creek 0 0 0 0 3 0
## Stepney 0 0 0 26 0 0
## Stirling 48 0 0 87 0 153
## Stoneville 0 0 0 0 0 50
## Stonyfell 0 0 0 37 0 0
## Strathewen 0 0 0 0 3 0
## Strathfield 0 389 0 0 0 0
## Strathfield South 0 57 0 0 0 0
## Strathmore 0 0 0 0 244 0
## Strathmore Heights 0 0 0 0 20 0
## Strathtulloh 0 0 0 0 10 0
## Stratton 0 0 0 0 0 65
## Stretton 0 0 63 0 0 0
## Sturt 0 0 0 65 0 0
## Subiaco 0 0 0 0 0 273
## Success 0 0 0 0 0 176
## Summer Hill 0 166 0 0 0 0
## Summertown 0 0 0 12 0 0
## Sumner 0 0 18 0 0 0
## Sunbury 0 0 0 0 1112 0
## Sunnybank 0 0 141 0 0 0
## Sunnybank Hills 0 0 301 0 0 0
## Sunshine 0 0 0 0 235 0
## Sunshine North 0 0 0 0 192 0
## Sunshine West 0 0 0 0 322 0
## Surrey Downs 0 0 0 91 0 0
## Surrey Hills 0 0 0 0 349 0
## Surry Hills 0 500 0 0 0 0
## Sutherland 0 388 0 0 0 0
## Swan View 0 0 0 0 0 144
## Swanbourne 0 0 0 0 0 102
## Sydenham 0 20 0 0 200 0
## Sydney 0 411 0 0 0 0
## Sydney Olympic Park 0 39 0 0 0 0
## Sylvania 0 174 0 0 0 0
## Sylvania Waters 0 69 0 0 0 0
## Symonston 3 0 0 0 0 0
## Taigum 0 0 162 0 0 0
## Tamarama 0 41 0 0 0 0
## Taperoo 0 0 0 77 0 0
## Tapping 0 0 0 0 0 217
## Taren Point 0 27 0 0 0 0
## Taringa 0 0 317 0 0 0
## Tarneit 0 0 0 0 1203 0
## Tarragindi 0 0 322 0 0 0
## Tarrawarra 0 0 0 0 1 0
## Tatachilla 0 0 0 2 0 0
## Taylor 41 0 0 0 0 0
## Taylors Hill 0 0 0 0 242 0
## Taylors Lakes 0 0 0 0 181 0
## Tea Tree Gully 0 0 0 100 0 0
## Tecoma 0 0 0 0 53 0
## Telopea 0 102 0 0 0 0
## Tempe 0 79 0 0 0 0
## Templestowe 0 0 0 0 371 0
## Templestowe Lower 0 0 0 0 301 0
## Teneriffe 0 0 288 0 0 0
## Tennyson 0 0 24 27 0 0
## Tennyson Point 0 25 0 0 0 0
## Teringie 0 0 0 18 0 0
## Terrey Hills 0 42 0 0 0 0
## Tharwa 1 0 0 0 0 0
## The Basin 0 0 0 0 88 0
## The Gap 0 0 447 0 0 0
## The Patch 0 0 0 0 21 0
## The Ponds 0 296 0 0 0 0
## The Rocks 0 3 0 0 0 0
## The Vines 0 0 0 0 0 122
## Thebarton 0 0 0 21 0 0
## Theodore 106 0 0 0 0 0
## Thomastown 0 0 0 0 351 0
## Thompson Beach 0 0 0 14 0 0
## Thornbury 0 0 0 0 488 0
## Thorngate 0 0 0 6 0 0
## Thornleigh 0 161 0 0 0 0
## Thornlie 0 0 0 0 0 421
## Three Bridges 0 0 0 0 3 0
## Throsby 39 0 0 0 0 0
## Tingalpa 0 0 228 0 0 0
## Tonsley 0 0 0 36 0 0
## Toolangi 0 0 0 0 4 0
## Toolern Vale 0 0 0 0 8 0
## Toongabbie 0 308 0 0 0 0
## Tooradin 0 0 0 0 24 0
## Toorak 0 0 0 0 469 0
## Toorak Gardens 0 0 0 72 0 0
## Tootgarook 0 0 0 0 148 0
## Toowong 0 0 401 0 0 0
## Torrens 50 0 0 0 0 0
## Torrens Park 0 0 0 82 0 0
## Torrensville 0 0 0 94 0 0
## Travancore 0 0 0 0 95 0
## Treeby 0 0 0 0 0 69
## Tregear 0 49 0 0 0 0
## Tremont 0 0 0 0 3 0
## Trigg 0 0 0 0 0 54
## Trinity Gardens 0 0 0 36 0 0
## Trott Park 0 0 0 63 0 0
## Truganina 0 0 0 0 665 0
## Tuart Hill 0 0 0 0 0 117
## Tuerong 0 0 0 0 1 0
## Tullamarine 0 0 0 0 160 0
## Turner 170 0 0 0 0 0
## Turramurra 0 502 0 0 0 0
## Turrella 0 30 0 0 0 0
## Tusmore 0 0 0 46 0 0
## Two Rocks 0 0 0 0 0 73
## Tyabb 0 0 0 0 81 0
## Tynong 0 0 0 0 8 0
## Tynong North 0 0 0 0 4 0
## Uleybury 0 0 0 6 0 0
## Ultimo 0 123 0 0 0 0
## Underdale 0 0 0 69 0 0
## Unley 0 0 0 122 0 0
## Unley Park 0 0 0 43 0 0
## Upper Brookfield 0 0 6 0 0 0
## Upper Ferntree Gully 0 0 0 0 75 0
## Upper Hermitage 0 0 0 3 0 0
## Upper Kedron 0 0 112 0 0 0
## Upper Mount Gravatt 0 0 244 0 0 0
## Upper Sturt 0 0 0 24 0 0
## Upper Swan 0 0 0 0 0 9
## Upwey 0 0 0 0 167 0
## Uraidla 0 0 0 8 0 0
## Uriarra Village 6 0 0 0 0 0
## Urrbrae 0 0 0 25 0 0
## Vale Park 0 0 0 70 0 0
## Valley View 0 0 0 155 0 0
## Vaucluse 0 219 0 0 0 0
## Vermont 0 0 0 0 229 0
## Vermont South 0 0 0 0 188 0
## Victoria Park 0 0 0 0 0 223
## Viewbank 0 0 0 0 134 0
## Villawood 0 54 0 0 0 0
## Virginia 0 0 91 39 0 0
## Vista 0 0 0 30 0 0
## Viveash 0 0 0 0 0 29
## Voyager Point 0 20 0 0 0 0
## Wacol 0 0 11 0 0 0
## Wahroonga 0 423 0 0 0 0
## Waikiki 0 0 0 0 0 268
## Waitara 0 211 0 0 0 0
## Wakeley 0 37 0 0 0 0
## Wakerley 0 0 252 0 0 0
## Walkerville 0 0 0 85 0 0
## Walkley Heights 0 0 0 50 0 0
## Walliston 0 0 0 0 0 24
## Walsh Bay 0 16 0 0 0 0
## Wandi 0 0 0 0 0 71
## Wandin East 0 0 0 0 5 0
## Wandin North 0 0 0 0 62 0
## Wanneroo 0 0 0 0 0 234
## Wanniassa 167 0 0 0 0 0
## Wantirna 0 0 0 0 251 0
## Wantirna South 0 0 0 0 376 0
## Waramanga 66 0 0 0 0 0
## Warburton 0 0 0 0 65 0
## Wareemba 0 27 0 0 0 0
## Warnbro 0 0 0 0 0 215
## Warneet 0 0 0 0 18 0
## Warradale 0 0 0 193 0 0
## Warrandyte 0 0 0 0 107 0
## Warrandyte South 0 0 0 0 12 0
## Warranwood 0 0 0 0 78 0
## Warrawee 0 78 0 0 0 0
## Warriewood 0 270 0 0 0 0
## Warwick 0 0 0 0 0 98
## Warwick Farm 0 81 0 0 0 0
## Waterfall 0 1 0 0 0 0
## Waterfall Gully 0 0 0 5 0 0
## Waterford 0 0 0 0 0 24
## Waterloo 0 304 0 0 0 0
## Waterloo Corner 0 0 0 16 0 0
## Watermans Bay 0 0 0 0 0 26
## Waterways 0 0 0 0 30 0
## Watson 225 0 0 0 0 0
## Watsonia 0 0 0 0 137 0
## Watsonia North 0 0 0 0 73 0
## Watsons Bay 0 13 0 0 0 0
## Watsons Creek 0 0 0 0 1 0
## Wattle Glen 0 0 0 0 46 0
## Wattle Grove 0 132 0 0 0 104
## Wattle Park 0 0 0 48 0 0
## Wavell Heights 0 0 340 0 0 0
## Waverley 0 104 0 0 0 0
## Waverton 0 73 0 0 0 0
## Wayville 0 0 0 47 0 0
## Wedderburn 0 7 0 0 0 0
## Weetangera 50 0 0 0 0 0
## Weir Views 0 0 0 0 43 0
## Welland 0 0 0 13 0 0
## Wellard 0 0 0 0 0 193
## Wembley 0 0 0 0 0 290
## Wembley Downs 0 0 0 0 0 145
## Wentworth Point 0 452 0 0 0 0
## Wentworthville 0 214 0 0 0 0
## Werribee 0 0 0 0 1163 0
## Werribee South 0 0 0 0 38 0
## Werrington 0 126 0 0 0 0
## Werrington County 0 86 0 0 0 0
## Werrington Downs 0 64 0 0 0 0
## Wesburn 0 0 0 0 20 0
## West Beach 0 0 0 134 0 0
## West Croydon 0 0 0 86 0 0
## West Footscray 0 0 0 0 321 0
## West Hindmarsh 0 0 0 23 0 0
## West Hoxton 0 92 0 0 0 0
## West Lakes 0 0 0 181 0 0
## West Lakes Shore 0 0 0 94 0 0
## West Leederville 0 0 0 0 0 135
## West Melbourne 0 0 0 0 189 0
## West Pennant Hills 0 248 0 0 0 0
## West Perth 0 0 0 0 0 218
## West Pymble 0 83 0 0 0 0
## West Richmond 0 0 0 28 0 0
## West Ryde 0 252 0 0 0 0
## West Swan 0 0 0 0 0 7
## Westbourne Park 0 0 0 54 0 0
## Westlake 0 0 119 0 0 0
## Westleigh 0 98 0 0 0 0
## Westmead 0 235 0 0 0 0
## Westmeadows 0 0 0 0 156 0
## Westminster 0 0 0 0 0 110
## Weston 91 0 0 0 0 0
## Wetherill Park 0 70 0 0 0 0
## Whalan 0 65 0 0 0 0
## Whale Beach 0 21 0 0 0 0
## Wheeler Heights 0 52 0 0 0 0
## Wheelers Hill 0 0 0 0 331 0
## Whitby 0 0 0 0 0 19
## White Gum Valley 0 0 0 0 0 83
## Whites Valley 0 0 0 2 0 0
## Whittlesea 0 0 0 0 169 0
## Wiley Park 0 125 0 0 0 0
## Willagee 0 0 0 0 0 182
## Willaston 0 0 0 109 0 0
## Willetton 0 0 0 0 0 319
## Williams Landing 0 0 0 0 181 0
## Williamstown 0 0 0 0 405 0
## Williamstown North 0 0 0 0 12 0
## Willmot 0 33 0 0 0 0
## Willoughby 0 274 0 0 0 0
## Willunga 0 0 0 73 0 0
## Willunga South 0 0 0 3 0 0
## Wilson 0 0 0 0 0 110
## Wilston 0 0 99 0 0 0
## Windsor 0 0 220 0 130 0
## Windsor Gardens 0 0 0 152 0 0
## Wingfield 0 0 0 7 0 0
## Winston Hills 0 221 0 0 0 0
## Winthrop 0 0 0 0 0 108
## Wishart 0 0 206 0 0 0
## Wollert 0 0 0 0 691 0
## Wolli Creek 0 227 0 0 0 0
## Wollstonecraft 0 200 0 0 0 0
## Wonga Park 0 0 0 0 58 0
## Woodbine 0 54 0 0 0 0
## Woodbridge 0 0 0 0 0 32
## Woodcroft 0 81 0 234 0 0
## Woodforde 0 0 0 22 0 0
## Woodlands 0 0 0 0 0 71
## Woodpark 0 10 0 0 0 0
## Woodside 0 0 0 71 0 0
## Woodstock 0 0 0 0 2 0
## Woodvale 0 0 0 0 0 188
## Woodville 0 0 0 53 0 0
## Woodville Gardens 0 0 0 25 0 0
## Woodville North 0 0 0 76 0 0
## Woodville Park 0 0 0 38 0 0
## Woodville South 0 0 0 98 0 0
## Woodville West 0 0 0 101 0 0
## Woollahra 0 295 0 0 0 0
## Woolloomooloo 0 91 0 0 0 0
## Woolloongabba 0 0 150 0 0 0
## Woolooware 0 123 0 0 0 0
## Wooloowin 0 0 121 0 0 0
## Woolwich 0 5 0 0 0 0
## Woori Yallock 0 0 0 0 75 0
## Wooroloo 0 0 0 0 0 15
## Woronora 0 44 0 0 0 0
## Woronora Heights 0 42 0 0 0 0
## Wright 122 0 0 0 0 0
## Wungong 0 0 0 0 0 5
## Wyndham Vale 0 0 0 0 561 0
## Wynn Vale 0 0 0 187 0 0
## Wynnum 0 0 487 0 0 0
## Wynnum West 0 0 361 0 0 0
## Yagoona 0 223 0 0 0 0
## Yallambie 0 0 0 0 66 0
## Yan Yean 0 0 0 0 4 0
## Yanchep 0 0 0 0 0 226
## Yangebup 0 0 0 0 0 155
## Yannathan 0 0 0 0 2 0
## Yarra Glen 0 0 0 0 67 0
## Yarra Junction 0 0 0 0 90 0
## Yarralumla 100 0 0 0 0 0
## Yarrambat 0 0 0 0 19 0
## Yarraville 0 0 0 0 417 0
## Yarrawarrah 0 59 0 0 0 0
## Yatala Vale 0 0 0 2 0 0
## Yattalunga 0 0 0 3 0 0
## Yeerongpilly 0 0 64 0 0 0
## Yellingbo 0 0 0 0 9 0
## Yennora 0 12 0 0 0 0
## Yering 0 0 0 0 1 0
## Yeronga 0 0 218 0 0 0
## Yokine 0 0 0 0 0 251
## Yowie Bay 0 48 0 0 0 0
## Yuroke 0 0 0 0 1 0
## Zetland 0 269 0 0 0 0
## Zillmere 0 0 282 0 0 0Visualisation
Plotting a boxplot for the bedrooms variable
boxplot(rawdata.df$bedrooms,xlab = "bedrooms", horizontal = TRUE)
Plotting barplots for the property sales by states and also by property type
par(mfrow=c(1,2))
statesprice <- table(rawdata.df$state)
barplot(statesprice, col="lightgreen", main = "Property Sales by States", xlab = "State", ylab = "Price")
typeprice <- table(rawdata.df$property_type)
barplot(typeprice, col = "lightblue", main = "Property Sales by Property Type", xlab = "Property Type", ylab = "Price")
Plotting a ggplot representing the sales with respect to city name
ggplot(rawdata.df, aes(factor(city_name), fill=factor(city_name))) + geom_bar() +ggtitle("Properties sold - Cities-Wise")
Further modification to the above ggplot to define the property types
ggplot(rawdata.df)+geom_bar(aes(x=state, colour=property_type),fill = NA, position="identity") + ggtitle(" Sales illustrating the Property types")
Plotting a qplot showing the state wise price of the properties sold
qplot(state, price, data = rawdata.df, geom="jitter")
ggplot(data=rawdata.df,mapping=aes(x=date_sold, y=property_type, color=state))+geom_point()+geom_smooth()## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
Data Cleaning and transformation
Creating a dummy variable named ‘dummy’ with value 1 if the price has a NULL value and a o therwise.
rawdata.df$dummy <- ifelse(rawdata.df$price == "NULL", 1, 0)
head(rawdata.df)Converting the invalid (NULL here) values for price variable to ‘NA’, as if they were missing values and also the invalid bedroom values (0 here) to ‘NA’, which can be treated further using missing value treatment.
rawdata.df <- mutate(rawdata.df, price = na_if(price, 'NULL'), bedrooms = ifelse(bedrooms==0, NA, bedrooms))
rawdata.dfUsing apply function to check for any NA’s in the data set
apply(is.na(rawdata.df), 2, sum)## date_sold price suburb city_name state
## 0 62508 0 0 0
## lat lon bedrooms property_type loc_pid
## 0 0 215 0 0
## lga_pid dummy
## 0 0We can see that there are 62508 observations of the price variable listed as NULL. Also, there are 215 observations from the bedrooms variable listed as 0. These might be the properties with no bedrooms (like a granny flats), or the data (no of bedrooms), not specified.
Plotting the missing values of the data set
mice_plot <- aggr(rawdata.df, col= c('navyblue','yellow'), numbers = TRUE, sortVars = TRUE, labels = names(rawdata.df), cex.axis=.7,gap=3,ylab=c("missing data","pattern"))## Warning in plot.aggr(res, ...): not enough horizontal space to display
## frequencies
##
## Variables sorted by number of missings:
## Variable Count
## price 0.1951338291
## bedrooms 0.0006711745
## date_sold 0.0000000000
## suburb 0.0000000000
## city_name 0.0000000000
## state 0.0000000000
## lat 0.0000000000
## lon 0.0000000000
## property_type 0.0000000000
## loc_pid 0.0000000000
## lga_pid 0.0000000000
## dummy 0.0000000000Converting the ‘character’ variables to ‘factors’
character_vars <- lapply(rawdata.df, class) == "character"
rawdata.df[, character_vars] <- lapply(rawdata.df[, character_vars], as.factor)
sapply(rawdata.df, class)## date_sold price suburb city_name state
## "factor" "factor" "factor" "factor" "factor"
## lat lon bedrooms property_type loc_pid
## "factor" "factor" "integer" "factor" "factor"
## lga_pid dummy
## "factor" "numeric"Converting the date_sold variable’s class to ‘Date’ and price variable’s class to ‘numeric’
rawdata.df$date_sold <- as.Date(rawdata.df$date_sold)
rawdata.df$price <- as.numeric(rawdata.df$price)
sapply(rawdata.df, class)## date_sold price suburb city_name state
## "Date" "numeric" "factor" "factor" "factor"
## lat lon bedrooms property_type loc_pid
## "factor" "factor" "integer" "factor" "factor"
## lga_pid dummy
## "factor" "numeric"Plotting a scatter plot for the data set
pairs(rawdata.df)
Adding month and year variables by retrieving month and year from the date_sold variable to the data set
rawdata.df <- rawdata.df %>%
mutate(month = month(date_sold))
rawdata.df <- rawdata.df %>%
mutate(year = year(date_sold))
str(rawdata.df)## 'data.frame': 320334 obs. of 14 variables:
## $ date_sold : Date, format: "2018-09-18" "2018-09-24" ...
## $ price : num NA NA 1904 2240 1408 ...
## $ suburb : Factor w/ 2028 levels "Abbotsbury","Abbotsford",..: 491 491 491 491 491 491 491 491 491 491 ...
## $ city_name : Factor w/ 6 levels "Adelaide","Brisbane",..: 6 6 6 6 6 6 6 6 6 6 ...
## $ state : Factor w/ 6 levels "ACT","NSW","QLD",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ lat : Factor w/ 269509 levels "-27.28698156",..: 99297 99896 99052 100769 100848 99280 100071 101140 99690 101010 ...
## $ lon : Factor w/ 270872 levels "115.582727","115.583492",..: 235473 235215 234836 234651 234357 234804 234969 234369 234992 234279 ...
## $ bedrooms : int 3 3 2 3 3 2 3 2 3 3 ...
## $ property_type: Factor w/ 3 levels "house","townhouse",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ loc_pid : Factor w/ 2122 levels "ACT101","ACT102",..: 132 132 132 132 132 132 132 132 132 132 ...
## $ lga_pid : Factor w/ 115 levels "ACT","BRIS1",..: 9 9 9 9 9 9 9 9 9 9 ...
## $ dummy : num 1 1 0 0 0 0 1 0 0 0 ...
## $ month : num 9 9 9 9 10 10 10 10 10 10 ...
## $ year : num 2018 2018 2018 2018 2018 ...summary(rawdata.df)## date_sold price suburb city_name
## Min. :2018-09-02 Min. : 1 Pakenham : 1818 Adelaide : 32857
## 1st Qu.:2019-03-05 1st Qu.: 3474 Craigieburn: 1502 Brisbane : 32240
## Median :2019-08-19 Median : 5793 Point Cook : 1440 Canberra : 11101
## Mean :2019-08-08 Mean : 5478 Melbourne : 1401 Melbourne:119180
## 3rd Qu.:2020-01-14 3rd Qu.: 7806 Frankston : 1344 Perth : 39661
## Max. :2020-07-16 Max. :10031 Brighton : 1206 Sydney : 85295
## NA's :62508 (Other) :311623
## state lat lon bedrooms
## ACT: 11101 NULL : 78 NULL : 78 Min. :1.000
## NSW: 85295 -34.93047917: 64 138.60190218: 64 1st Qu.:2.000
## QLD: 32240 -35.181563 : 45 149.130712 : 45 Median :3.000
## SA : 32857 -34.93041075: 43 138.60129828: 43 Mean :3.111
## VIC:119180 -33.75838908: 40 150.7173506 : 40 3rd Qu.:4.000
## WA : 39661 -37.78466 : 38 144.93829743: 37 Max. :5.000
## (Other) :320026 (Other) :320027 NA's :215
## property_type loc_pid lga_pid dummy
## house :219552 VIC2023: 1818 ACT : 11101 Min. :0.0000
## townhouse: 24528 VIC660 : 1502 BRIS2 : 8672 1st Qu.:0.0000
## unit : 76254 VIC2082: 1440 BRIS3 : 7914 Median :0.0000
## VIC1634: 1401 VIC127 : 7799 Mean :0.1951
## VIC939 : 1344 NSW329 : 6672 3rd Qu.:0.0000
## VIC2453: 1203 NSW283 : 6530 Max. :1.0000
## (Other):311626 (Other):271646
## month year
## Min. : 1.000 Min. :2018
## 1st Qu.: 3.000 1st Qu.:2019
## Median : 7.000 Median :2019
## Mean : 6.729 Mean :2019
## 3rd Qu.:10.000 3rd Qu.:2020
## Max. :12.000 Max. :2020
## rawdata.df <- rawdata.df %>%
mutate(qtr = paste0(substring(year(date_sold),2,4),"/0",quarter(date_sold)))
str(rawdata.df)## 'data.frame': 320334 obs. of 15 variables:
## $ date_sold : Date, format: "2018-09-18" "2018-09-24" ...
## $ price : num NA NA 1904 2240 1408 ...
## $ suburb : Factor w/ 2028 levels "Abbotsbury","Abbotsford",..: 491 491 491 491 491 491 491 491 491 491 ...
## $ city_name : Factor w/ 6 levels "Adelaide","Brisbane",..: 6 6 6 6 6 6 6 6 6 6 ...
## $ state : Factor w/ 6 levels "ACT","NSW","QLD",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ lat : Factor w/ 269509 levels "-27.28698156",..: 99297 99896 99052 100769 100848 99280 100071 101140 99690 101010 ...
## $ lon : Factor w/ 270872 levels "115.582727","115.583492",..: 235473 235215 234836 234651 234357 234804 234969 234369 234992 234279 ...
## $ bedrooms : int 3 3 2 3 3 2 3 2 3 3 ...
## $ property_type: Factor w/ 3 levels "house","townhouse",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ loc_pid : Factor w/ 2122 levels "ACT101","ACT102",..: 132 132 132 132 132 132 132 132 132 132 ...
## $ lga_pid : Factor w/ 115 levels "ACT","BRIS1",..: 9 9 9 9 9 9 9 9 9 9 ...
## $ dummy : num 1 1 0 0 0 0 1 0 0 0 ...
## $ month : num 9 9 9 9 10 10 10 10 10 10 ...
## $ year : num 2018 2018 2018 2018 2018 ...
## $ qtr : chr "018/03" "018/03" "018/03" "018/03" ...Imputing the NAs in the price variable with median price of that particular state and property type.
rawdata.df <- rawdata.df %>%
group_by(state, property_type) %>%
mutate(price=replace(price, is.na(price), median(price, na.rm=TRUE)))
head(rawdata.df, 50)A sample count_missing function to find out the missing values in our further analysis.
count_missing = function(df){
sapply(df, FUN=function(col) sum(is.na(col)))
}
nacounts <- count_missing(rawdata.df)
hasNA=which(nacounts >0)
nacounts[hasNA]## bedrooms
## 215To check for number of different types of properties sold per state (Contingency Tables)
ptype <- xtabs(~ city_name+property_type+bedrooms, data = rawdata.df)
ptype## , , bedrooms = 1
##
## property_type
## city_name house townhouse unit
## Adelaide 92 4 492
## Brisbane 49 3 1182
## Canberra 23 34 891
## Melbourne 243 45 5942
## Perth 126 18 839
## Sydney 192 8 6658
##
## , , bedrooms = 2
##
## property_type
## city_name house townhouse unit
## Adelaide 2005 342 3194
## Brisbane 1137 545 4499
## Canberra 282 414 1447
## Melbourne 5108 3212 16581
## Perth 1494 228 2370
## Sydney 3017 1014 19239
##
## , , bedrooms = 3
##
## property_type
## city_name house townhouse unit
## Adelaide 16384 667 481
## Brisbane 8877 2891 1243
## Canberra 2928 903 308
## Melbourne 36151 6578 5232
## Perth 13355 863 928
## Sydney 18492 2971 4578
##
## , , bedrooms = 4
##
## property_type
## city_name house townhouse unit
## Adelaide 7643 55 0
## Brisbane 8183 248 0
## Canberra 3078 133 0
## Melbourne 31511 2412 0
## Perth 16943 113 0
## Sydney 20304 684 0
##
## , , bedrooms = 5
##
## property_type
## city_name house townhouse unit
## Adelaide 1474 2 0
## Brisbane 3367 7 0
## Canberra 650 0 0
## Melbourne 6030 97 0
## Perth 2369 2 0
## Sydney 7984 31 0Plotting a boxplot to look for outliers after the NULLs in price variable are replaced by NA’s
boxplot(ptype, data=rawdata.df, xlab = "city_name+property_type+bedrooms", ylab= "Price")
ggplot(data = rawdata.df, aes(x= price, y = city_name, colour = bedrooms))+geom_point()
Plotting yearly property sales.
rawdata.df %>%
ggplot(aes(x = year, y = price)) +
geom_bar(stat = "identity", fill = "darkorchid4") +
facet_wrap(~ year, ncol = 3) +
labs(title = "Yearly Property Sales",
subtitle = "Data plotted by year",
y = "price",
x = "Year") + theme_bw(base_size = 15)
Plotting ggpairs for properties sold and price using the date_sold and price variables.
ggpairs(rawdata.df, columns = 1:2, ggplot2::aes(colour=state)) 
We can see that there is a decrease in the property price for the properties in many states.
library(hrbrthemes)## NOTE: Either Arial Narrow or Roboto Condensed fonts are required to use these themes.## Please use hrbrthemes::import_roboto_condensed() to install Roboto Condensed and## if Arial Narrow is not on your system, please see https://bit.ly/arialnarrowrawdata.df %>%
tail(10) %>%
ggplot( aes(x=date_sold, y=price)) +
geom_line( color="grey") +
geom_point(shape=21, color="black", fill="#69b3a2", size=6) +
theme_ipsum() +
ggtitle("Property Sales")## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): font family not
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ggplot for an yearly median price of the properties sold state wise.
ggplot(data = rawdata.df, aes(x = year, y = price, group = state, color=state)) + ggtitle("Yearly, State-Wise Median Price of Properties Sold ") +
stat_summary(geom = "line", fun.y = median)## Warning: `fun.y` is deprecated. Use `fun` instead.
ggplot for an yearly median price of the property_types sold, state-wise
ggplot(data = rawdata.df, aes(x = property_type, y = year, group = state, color=state)) + ggtitle("Yearly, State-Wise Median Price of Property Types Sold ") +
stat_summary(geom = "line", fun.x = mean)## Warning: Ignoring unknown parameters: fun.x## No summary function supplied, defaulting to `mean_se()`
Plotting Quartely state-wise median price of the properties sold
ggplot(data = rawdata.df, aes(x = qtr, y = price, group = state, color=state)) + ggtitle("Quarterly State-Wise Median Price of Properties Sold ") +
stat_summary(geom = "line", fun.y = median)## Warning: `fun.y` is deprecated. Use `fun` instead.
Quarterly, state-wise median price of the propery_types sold
ggplot(data = rawdata.df, aes(x = qtr, y = property_type, group = state, color=state)) + ggtitle("Quarterly, State-Wise Median Price of Property types Sold ") +
stat_summary(geom = "line", fun.y = mean)## Warning: `fun.y` is deprecated. Use `fun` instead.
Barplot to show the yearly, state-wise median price of the properties sold
ggplot(data = rawdata.df, aes(x = property_type, y = year, group = state, color=state)) + ggtitle("Yearly, State-Wise Median Price of Properties Sold ") +
geom_bar(stat='identity')
We can conclude that there is a visible reduction in the property sales during the Quarter 1 and Quarter 2 of 2020, which is the time COVID-19 is declared as a Pandemic. From the beginning of Quarter 2, we can notice a visible demand/increase in the property market which is a good sign that the market is improving.